Control Strategies for Under-Frequency Load Shedding

8/12/2019 Control Strategies for Under-Frequency Load Shedding

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eehpower systemslaboratory

Ifigeneia Stefanidou Maria Zerva

Control Strategies for Underfrequency LoadShedding

Interaction of Distributed Generation with Load Shedding

Decentralized UnderFrequency Load Shedding of HouseholdLoads

Semester Thesis

PSL0904

EEH Power Systems Laboratory

Swiss Federal Institute of Technology (ETH) Zurich

Expert: Prof. Dr. Goran Andersson

Supervisor: Dipl.Ing. Stephan Koch

Zurich, September 3, 2009


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Abstract

The current approach of the Union for the Coordination of Transmission of Electricity for

counteracting large frequency deviations due to lack of generation is the UnderFrequency

Load Shedding scheme. The UnderFrequency Load Shedding scheme is the interruption of

the power supply to a predefined percentage of customers when certain frequency deviations

occur in the system. The drawback of the UnderFrequency Load Shedding scheme is that

loss of load in entire areas occurs, since entire feeders are disconnected from the grid,

and the interaction of the increasing Distributed Generation present in the system is not

considered. The scope of the present study is to evaluate the impact of the Distributed

Generation on the stable and secure electricity transmission systems operation and assess

the performance of the proposed UnderFrequency Household Load Shedding scheme. The

UnderFrequency Household Load Shedding scheme provides a flexible and decentralized

way of mitigation.


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I. Stefanidou & M. Zerva 0. CONTENTS

Contents

1 Introduction 9

2 UCTE Conventional Load Shedding 11

2.1 Reference Power System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.2 Stabilization of the System Frequency . . . . . . . . . . . . . . . . . . . . . 12

2.3 System Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.3.1 Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3.2 Dynamics of generators . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3.3 Frequency Dependency of Loads . . . . . . . . . . . . . . . . . . . . 15

2.3.4 Primary Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3.5 Load Shedding Mechanism . . . . . . . . . . . . . . . . . . . . . . . 17

2.3.6 Frequency Response Model . . . . . . . . . . . . . . . . . . . . . . . 18

3 Interaction of Distributed Generation with Load Shedding 20

3.1 Distributed Generation in Germany . . . . . . . . . . . . . . . . . . . . . . 20

3.2 Penetration Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.3 Distributed Generation Power Output . . . . . . . . . . . . . . . . . . . . 23

3.4 Frequency Response Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

4 Household Load Shedding 27

4.1 Household load profile during the day . . . . . . . . . . . . . . . . . . . . . 27

4.2 The potential of UnderFrequency Household Load Shedding . . . . . . . . 30

4.3 UnderFrequency Household Load Shedding as a complement to Conven

tional Load Shedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

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4.3.1 Frequency response model . . . . . . . . . . . . . . . . . . . . . . . 35

4.4 UnderFrequency Household Load Shedding for substitution of ConventionalLoad Shedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.4.1 Frequency Response Model . . . . . . . . . . . . . . . . . . . . . . . 38

5 Reference Cases Results 41

5.1 Reference Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

5.1.1 Summer scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

5.1.2 Winter scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

5.2.1 Case 1 Summer scenario, 11 a.m. . . . . . . . . . . . . . . . . . . 44

5.2.2 Case 2 Summer scenario, 3 a.m. . . . . . . . . . . . . . . . . . . . 50

5.2.3 Case 3 Winter scenario, 11 a.m. . . . . . . . . . . . . . . . . . . . 55

5.2.4 Case 4 Winter scenario, 3 a.m. . . . . . . . . . . . . . . . . . . . . 60

6 Conclusions 65

References 67


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I. Stefanidou & M. Zerva 0. LIST OF FIGURES

List of Figures

1 Interconnected UCTE Power System [1]. . . . . . . . . . . . . . . . . . . . 11

2 Total system inertia of the interconnected system. . . . . . . . . . . . . . . 15

3 Frequency Dependency of Loads. . . . . . . . . . . . . . . . . . . . . . . . 16

4 Primary Control. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

5 Load Shedding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

6 Frequency Response Model. . . . . . . . . . . . . . . . . . . . . . . . . . . 19

7 Load density (left) and DG share (right) of each State. . . . . . . . . . . . 22

8 Wind (left) [13] and Solar (right) potential of Germany [14]. . . . . . . . . 25

9 The power system frequency response model, considering the DG loss. . . . 26

10 Share of consumption of the household appliances [5]. . . . . . . . . . . . . 28

11 Power consumption of each household appliance group over the day. . . . . 29

12 Sheddable household load in Germany. . . . . . . . . . . . . . . . . . . . . 33

13 HLS scheme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

14 Frequency response model including the HLS mechanism. . . . . . . . . . . 36

15 HLS mechanism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

16 Set of flip flops. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

17 Frequency response model including the substitutional HLS mechanism. . . 39

18 Substitutional HLS mechanism. . . . . . . . . . . . . . . . . . . . . . . . . 40

19 Physical and planned flows within the UCTE [6]. . . . . . . . . . . . . . . 41

20 Summer scenario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

21 Winter scenario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

22 Case 1 Dynamic response including DG. . . . . . . . . . . . . . . . . . . 46

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I. Stefanidou & M. Zerva 0. LIST OF FIGURES

23 Case 1 Dynamic response with different household participations. . . . . 46

24 Case 1 Dynamic response without the HLS mechanism and with the participation of 10% of the German households. . . . . . . . . . . . . . . . . . 47

25 Case 1 Dynamic response with 30% and 50% of the German households

participating in the HLS scheme. . . . . . . . . . . . . . . . . . . . . . . . 47



27 Case 1 Dynamic response with HLS scheme substituting the CLS mecha

nism for Germany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

28 Case 1 Dynamic response with HLS scheme substituting the CLS mecha

nism for Germany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49


30 Case 2 Dynamic response with different household participation. . . . . . 51

31 Case 2 Dynamic response without the HLS mechanism and with the par

ticipation of 10% of the German households. . . . . . . . . . . . . . . . . . 52





34 Case 2 Dynamic response with the HLS scheme substituting the CLS

mechanism for Germany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53







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47 Case 4 Dynamic response with 70% and 100% of the German householdsparticipating in the HLS scheme. . . . . . . . . . . . . . . . . . . . . . . . 63






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List of Tables

1 Load Shedding stages according to the UCTE Handbook [2]. . . . . . . . . 13

2 Type of Loads. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3 DG installed capacity and penetration scenarios for 2010 and 2020. . . . . 23

4 Power Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5 Comfort loss of each appliance category. . . . . . . . . . . . . . . . . . . . 31

6 Sheddable load per German household. . . . . . . . . . . . . . . . . . . . . 34

7 Case 1 Power data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

8 Case 2 Power data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

9 Case 3 Power data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

10 Case 4 Power data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60


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I. Stefanidou & M. Zerva 1. Introduction

1 Introduction

Power systems provide a vital infrastructure for the functioning of todays societies which

have become increasingly dependent on reliable and secure supply of electricity. Their

operation and structure have significantly evolved over the years incorporating market

mechanisms in the initially monopolistic trade of electricity.

The deregulation of the electricity markets has created challenges concerning the operation

of the systems, while the goal is still to maintain the reliability and the security of supply.

The decoupling of the electricity generation, transmission, distribution and retail and theinvolvement of more participants has led to a more complex environment, both economical

and technological. The interconnection links between different countries do no more serve

emergency but regular trading purposes, resulting in the increasing probability of the

overloading of the tielines. A possible disturbance now affects the whole interconnected

system and can be spread over long distances within seconds and, if not eliminated, it may

result in a complete system collapse.

The liberalization of electricity markets provides free market access to many various par

ticipants, while the trend of the last decades towards reducing greenhouse gas emissionsleads to the development of mainly small scaled, 2free sources for energy production,

which are strongly supported by legislation. Consequently, the integration of distributed

sources into the networks leads to the modification of the structure of the electric power

systems and the initial unidirectional power flows. Therefore, as a side effect of the develop

ment of Distributed Generation units, the traditional protection and control mechanisms

of the power systems, which do not consider the Distributed Generation (DG), turn to be

insufficient or inappropriate.

The security and the quality of supply are the primary goal of the electric power systems,

considering the strong impacts that a disturbance may have on the society and the fact

that electricity as a product cannot be stored on a large scale. However, the security of

power systems is jeopardized by the previously mentioned changes of their operation and

structure. The impact of the Distributed Generation penetration can be assessed by quan

tifying the Distributed Generation and modelling its interaction with the power system.

Future scenarios for increasing the Distributed Generation imply the need for a further

modification of the control methods used under normal or emergency conditions.

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I. Stefanidou & M. Zerva 1. Introduction

The proposed method is the UnderFrequency Household Load Shedding (UFHLS) which

includes the frequency dependent, automatic disconnection of nonvital individual house

hold loads. The UFHLS can be implemented either together with the present control mech

anisms in order to act complementary or for a complete substitution of the existing control

schemes. In each case, the proposed scheme is decentralized in order for the system to

be robust to imminent disturbances, while the shedding of household loads is realized

stepbystep, according to predefined frequency thresholds. Individual household loads are

disconnected with priority to the uncritical ones that are less vital for the consumers, so

as for the interruption of supply to be least observed by the consumers.

The implementation of the UFHLS scheme should ensure the robustness of the power

systems. Therefore, an automatic mechanism is needed in order for the suitable load re

ductions to be realized in every disturbance case, considering the capacity of the system

and the comfort loss for the consumers at any time.

Germany, being among the leaders in technological innovation and a major UCTE member

country, provides a good paradigm for the assessment of the performance of the proposed

HLS mechanism and the interaction of DG in the context of UCTE. For these reasons,

data for the German households and DG are used for the derivation of reference scenarios

appropriate for the simulation of the UCTE power system frequency response in case of acontingency.

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I. Stefanidou & M. Zerva 2. UCTE Conventional Load Shedding

2 UCTE Conventional Load

Shedding

2.1 Reference Power System

The Union for the Coordination of Transmission of Electricity (UCTE) is an association

of the Transmission System Operators (TSOs) of 24 European countries (Figure 1). The

interconnected system handled by the UCTE comprises of 220000 Km of transmission

lines and a total installed capacity of 640 GW.

Figure 1: Interconnected UCTE Power System [1].

The interconnected power systems of the membercountries of the UCTE operate syn

chronously at the nominal frequency of 50 Hz. The UCTE interconnected system was

initially introduced for the cooperation of the TSOs in emergency cases. Over the past

few years the electricity market across Europe has been redesigned and the trade of elec

tricity among European countries has been developed. The use of the interconnections

between countries has shifted from emergency to trade purposes, resulting in the opera

tion of the interconnection links to their limits and, thus, compromising the stability and

the security of the UCTE power system. Therefore, the coordinated actions of the UCTE

membercountries are necessary in order to ensure the secure and reliable operation of the

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system.

The UCTE issues the UCTE Operation Handbook which is a set of technical and operational principles and rules ensuring the reliable performance of the interconnected high

voltage grids of the continental Europe. All UCTE members are bound to comply with

the UCTE and collectively contribute to the stabilization of the system in any emergency

case.

2.2 Stabilization of the System Frequency

Emergency situations within the UCTE power system are mainly indicated by the devia

tions of the system frequency. Since the frequency is approximately equal in all participat

ing countries, the automatic response of the primary controllers in each membercountry

is triggered in order to stabilize the frequency. The secondary control acts then in order to

bring the system frequency back to its nominal value 1. In response to a quasisteadystate 2

frequency deviation of 200 mHz or more [2], the primary control reserves in each UCTE

membercountry are deactivated or activated, in order to restore the power balance of the

system. The primary controllers should be able to stabilize the system in case of a failureup to 3000 MW of the generating capacity in normal operation [2]. The contribution of

each membercountry to the primary reserves is proportional to the ratio of the electricity

produced over the total electricity production across the UCTE. In case that the extent of

the disturbance is higher than the capability of the primary controllers, additional measures

are required, such as the frequency sensitive triggering of load shedding.

The Load Shedding is triggered when the frequency drops to a predefined level, in order to

protect the power generating systems and avoid a major power system breakdown. During

a major disturbance, i.e. a loss of generation, and under emergency conditions when there isinsufficient generation capability for the current demand, the electrical supply is interrupted

to a certain number of consumers in each membercountry of the UCTE according to the

implemented Load Shedding scheme in order to prevent a total collapse of the UCTE

system.

1The secondary control is not regarded, since its dynamics are much slower and out of the scope of the

present study.2The quasisteadystate refers to a stable system frequency but not at the nominal value.

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Each TSO determines its shedding plan according to the rules of the UCTE. The TSOs of

the UCTE participate in the Load Shedding scheme irrespectively of the location of the

failure. The UCTE recommends that the Load Shedding is implemented in three steps and

involves the disconnection of feeders amounting to a predefined share of the load. The first

step of the Load Shedding is initiated at the frequency threshold of 49 Hz by disconnecting

the 1020% of the total load. The second and the third step are triggered at 48.7 Hz and

48.4 Hz, respectively, by disconnecting an additional 1015% of the initial load at each

step (see Table 1).

Frequency Thresholds Load Shedding

49.0 Hz 1020%

48.7 Hz 1015%

48.4 Hz 1015%

Table 1: Load Shedding stages according to the UCTE Handbook [2].

2.3 System Modeling

The interconnecting links among the membercountries of UCTE were traditionally used

under emergency conditions, while, nowadays, they also serve trading purposes and are

known as tielines. Besides the benefits of the interconnection of the power systems, the

regular trading of electricity results in a high possibility of the overloading of the tielines.

A disturbance within the UCTE can be spread over large distances and, in the worst case,

cause a total collapse of the interconnected system.

The power system frequency response model of the UCTE, including the Load Shedding

mechanism recommended by the UCTE, simulates the frequency deviations during normal

and emergency conditions. In order to study the power system of Germany, it is necessary to

also consider the behavior of the whole interconnected system, since the system frequency

is determined by the balance between the total generation and demand. Furthermore, the

power exchanges of the UCTE with other interconnected systems via DC or AC links

influence the frequency response in each membercountry, since a local disturbance can

cause a cascading series of outages within the interconnected system.

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=

0

2 (

) (2)

The respective block in the frequency response model describes the total system inertia

and the reflection of the power imbalances on the frequency deviations of the system

(Figure 2). The total system inertia constant is assumed to be equal to 5 seconds, while

the represents the cumulated power rating of the rotating synchronous machines in the

interconnected system under study.

dP

Subtract

Net Import

Load

Integrator

1

s

Generation

Gain

f0/(2*H*S) df

Figure 2: Total system inertia of the interconnected system.

2.3.3 Frequency Dependency of Loads

The frequency dependency of the active power of the loads is taken into account, since the

frequency deviation within a system influences the behavior of the loads. The industrialloads are mainly motors which can store the kinetic energy of their rotating masses. There

fore, a possible frequency drop during a disturbance can be partly stabilized by the stored

kinetic energy of the motors. The commercial and residential loads can also be frequency

dependent, depending on their structure.

Typical values describing the frequency dependency of the loads are expressed in per cent

of the load variation from the total load for one per cent of frequency deviation from the

nominal value (Table 2).

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Load Type dP/df (%/%) Representative Type Share

Residential 0.9 40%

Commercial 1.4 20%

Industrial 2.6 40%

Table 2: Type of Loads.

According to the proposed values for the load models, the frequency dependency of the

active power consumed by the loads can be described by the factor which equals to 1.6

( = 16). The respective block in the frequency response model describes the normalized

active power deviation of the loads resulting from a system frequency deviation (Figure 3).

Frequency deviation

df

Frequency dependent active power

dP1.66*S/f0

Figure 3: Frequency Dependency of Loads.

2.3.4 Primary Control

The primary controllers of the entire UCTE system can eliminate a disturbance caused by

a power deficit not higher than 3000 MW under normal conditions. The primary reserves

in each membercountry of the UCTE are proportional to its generation capacity [2]. In

case of a disturbance, the primary controllers of every country of the interconnected systemcontribute to its elimination. The speed droop characteristic of the interconnected system

under study represents the different operating points of the system. The speed droop of

the system is considered to be approximately equal to the total generated power at each

time instant.

The linearized dynamic modelling of the turbines of the primary reserves is essential, despite

the fact that the turbine controllers time constant is much smaller than the time constant of

the frequency dynamics of the system. The UCTE system is modeled as an onearea system,

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Load shed

LS

Load Shedding

df Share of load

load

Frequency

deviation

df

Figure 5: Load Shedding.

2.3.6 Frequency Response Model

The frequency response model is constructed by combining the previously analyzed mech

anisms (Figure 6). The inputs to the modeled power system of the interconnected areas arethe total generated power, the total consumed power and the net imports from neighboring

power systems at each time instant. In case of a disturbance, i.e. loss of generation or un

expected increase of the load, the power deficit is reflected on a system frequency deviation

by means of the generators dynamics and the system inertia constant. Subsequently, the

frequency deviation influences the active power consumption of the frequency dependent

loads and triggers the primary controllers and the load shedding mechanism, according to

the magnitude of the disturbance.

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f0

Turbine dynamics

1

7s+1

System

frequency

freq

Sum of f0+df

Sum of

loads of 24 UCTE countries

SaturationPrimary control

-1/(Spr*f0/S)

Net Import

loadLoad

1

s

Generationf0/(2*H*S)

Frequency dependency of Loads

1.66*S/f0

Conventional

Load Shedding

dfLoad Shed

Figure 6: Frequency Response Model.

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I. Stefanidou & M. Zerva 3. Interaction of Distributed Generation with Load Shedding

3 Interaction of Distributed

Generation with Load Shedding

The term Distributed Generation (DG) is used to characterize electric power sources with

small rating as compared to conventional power plants, which are connected to the dis

tribution grid, i.e. Medium and Low Voltage Level. Distributed Generation has faced a

significant growth, mainly due to the liberalization of the electricity market and the trend

for shifting the electricity production towards 2neutral energy sources for reducing

greenhouse gas emissions and mitigating climate change.

The DG, being mostly renewable energy sources, creates a number of uncertainties in the

power system, in terms of inability to precisely schedule the power injected into the grid.

Additionally, the renewable energy sources that are connected to the distribution grid can

not be directly controlled by the transmission system operators. In case of necessity for

activation of the Load Shedding mechanism due to an imminent disturbance, there is high

probability that additional loss of generation will occur. Feeders that are disconnected in

emergency cases may have Distributed Generation units connected to them, which causes

to the disconnection of the dispersed generation. Thus, the extent of the Distributed Generation loss in such cases should be quantified in order for the interaction to be evaluated.

3.1 Distributed Generation in Germany

The European Union has adopted certain measures for promoting renewable energy sources,

in view of the commitments of the Kyoto Protocol. Germany, as a Member State of the

EU has set specific targets for renewable energy penetration and has achieved to becomethe leader on the grounds of both installations and technical knowhow. In the case of

Germany, most common energy carriers for DG are wind, solar, biomass and to a limited

extent geothermal, hydro and gas power plants.

Four TSOs operate within Germany, i.e. Transpower Stromubertragungs GmbH (company

affiliated with E.ON) [4], Vattenfall Europe Transmission GmbH [5], RWE Transportnetz

Strom GmbH [6] and EnBW Transportnetze AG [7]. According to data published by the

TSOs, Germany has a total installed capacity of 137.5 GW. The renewable energy sources

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installations amount to 38029 MW, out of which 12245 MW are installations with a rating

smaller than 10 MW, connected to the low and medium voltage level.

The regionally different renewable energy potential leads to regional differences in the DG

installed capacity of the different energy carriers [8]. In the present study, the power plants

who receive the feedin tariff are divided according to the state of Germany to which they

belong to in order to correspond to the regional potential. Thus, in Northern Germany the

dominant energy carrier is wind, whereas in the Southern Germany DG is mostly solar

installations. Southern Germany has lower shares of DG due to the fact that solar instal

lations have significantly smaller rating and are not yet as developed as wind power units.

For biomass, gas and geothermal installations there is no clear geographical distinction.

Apart from the renewable energy source DG, nonrenewable smallscale Combined Heat

and Power (CHP) plants are also connected to the distribution levels and are disconnected

in the case of load shedding. However, the penetration levels are quite low and there is no

exact data available.

The raw data published by the TSOs concerning the power plants which receive a feedin

tariff have been sorted according to energy carrier, nominal installed capacity and postal

code. The installations data need to be further sorted per State in order for the relation

between the load density3

and the potential of each region to be also considered (Figure 7).The DG shares over the total DG capacity are higher in the Northern States of Germany due

to the high penetration of wind power plants. In States with high DG shares and relatively

low load density the risk of deteriorating the situation, by disconnecting significant amounts

of DG units together with a small portion of load, is higher.

3The load share is assumed to be equal to the population share of each State of Germany.

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Figure 7: Load density (left) and DG share (right) of each State.

3.2 Penetration Scenarios

Renewable energy source power plants are expected to further increase in the years to

come. In 2002 Germany set a goal to cover the 14% [9] of the electricity consumption

with renewable energy sources until 2008. The goal has been achieved (14.2%) [10] andhigher targets have been set. Increase of the DG is expected to substantially change the

structure of the electricity transmission and distribution grid, posing great ambiguity to

the effectiveness of the current control mechanisms; the load shedding mechanisms involves

the disconnection of feeders in case of lack of generation irrespectively of the DG units that

they may have connected to them.

The future possible growth of the DG is necessary to be considered in order to quantify the

future DG installations and assess the degree of interaction of the DG with the security

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the electricity consumption was 14.2%. The difference in the two percentages implies that

the load factors of the renewable energy source power plants are substantially limited by

weather conditions, regional potential and time of the day.

The data published by the TSOs concern either the installed capacity or total energy

production over a year. However, the effect of the DG in the system in emergency cases can

only be assessed by considering the instantaneous injected power from the DG installations,

rather than their installed capacity. The power output of each installation highly depends

on the type of the energy carrier, the weather conditions, the time of the day and the

potential of the region in which it is installed. Therefore, factors which reflect the potential

of each region and the maximum power output for each energy carrier are necessary. The

methodology followed in the present study in order for the factors to be derived is the

normalization of representative parameter for each energy carrier.

The parameter that limits the power output of wind power plants is mainly the wind speed.

The wind power potential of each region of Germany is derived based on statistical data

concerning the mean wind speed in each State for every month of the year. The mean

wind speed of every State in each month is divided by the maximum mean wind speed in

Germany over a year. The normalized wind speeds are considered as factors which scale

the wind power output. A factor of 1 is attributed to the region with the highest potentialand for the month with the highest mean wind speed.

As far as solar panels are concerned, the parameters taken into account are the mean

irradiation in each region during the year and the mean duration of sunshine. Similar to

wind power and based on statistical data, the factors for solar power correspond to the

normalized irradiation in each State (Figure 8). For the solar panels optimal inclination is

assumed, providing the opportunity to have the maximum possible power output.

For geothermal, hydro, gas and biomass power plants it is assumed that the power output

is independent of weather conditions, regional distribution and time of the day. Therefore,

uniform factors are considered to limit the power output and approximate their contribu

tion to the total Distributed Generation.

The factors calculated for each energy carrier are multiplied with the installed capacity,

and, therefore, the energy injected into the system is calculated for the time snapshots for

which UCTE publishes load and power exchange data (Table 4).

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Figure 8: Wind (left) [13] and Solar (right) potential of Germany [14].

Energy Carrier

OUTPUT (MW)

Winter Summer11 a.m 3 a.m 11 a.m 3 a.m

Solar 853.05 0 2202.51 0

Wind 5279.58 5279.58 3981.70 3981.70

Biomass 1684.62 1684.62 1684.62 1684.62

Geothermal 426.54 426.54 426.54 426.54

Hydro 2.90 2.90 2.90 2.90

Gas 512.06 512.06 512.06 512.06

Table 4: Power Output.

3.4 Frequency Response Model

The Distributed Generation loss at each load shedding stage is assumed to be 10% of

the total Distributed Generation output injected into the system at each time instant. In

the power system frequency response model (Figure 9) the Distributed Generation taken

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I. Stefanidou & M. Zerva 4. Household Load Shedding

4 Household Load Shedding

Underfrequency load shedding is traditionally triggered when the power system suffers

from a lack of generation, i.e. sudden loss of generation or increase of load. In order to

stabilize the frequency, entire feeders are disconnected from the grid, while unexpected

additional loss of generation may occur due to disconnection of Distributed Generation

connected to the distribution level. With increasing Distributed Generation the conven

tional underfrequency load shedding scheme cannot guarantee the stabilization of the

system, which could be avoided by the development of automated and locally controlled

load shedding schemes.

The UnderFrequency Household Load Shedding (HLS) is a decentralized scheme under

which households participate with small scale appliances in the grid control schemes. In the

case of an underfrequency disturbance, the appliance operation can be influenced by control

commands sent through a communication interface by a decentralized control system,

equipped with suitable control algorithms. Aiming to the minimum cost for the society

and to the minimum comfort loss for the consumers, a fast and graceful load reduction can

be achieved and a total system collapse can be prevented by shedding nonvital, individual

household loads.

The HLS scheme can act either as a complement to the Conventional Load Shedding (CLS)

mechanism, and, thus, delay or even avoid its triggering, or for complete substitution of

the CLS, depending on the implementation of the scheme. The potential of the HLS is

studied, in compliance with the quantified Distributed Generation, for the household load

of Germany.

4.1 Household load profile during the day

The household load in each time instant is highly dependent on the weather conditions,

the time of the day and the lifestyle in the region under study. Germany has a total of

39700000 households [15] which according to statistical data are responsible for approx

imately 30% [5] of the total load of Germany in average. In 2008, the total electricity

consumption in Germany was 557162 GWh [1]. Considering the percentage share of the

household consumption over the total consumption of Germany, German households ap

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proximately consumed in 2008 167149 GWh, which corresponds to an average household

load of 19081 MW.

For load shedding purposes the vital load of each household is not considered, whereas

for the nonvital appliances their specific consumption has to be quantified. Due to their

volatility, the devices within a household are grouped according to their similarities in their

characteristics, i.e. usage, and classified considering the utilization and comfort loss over

the day.

The German household appliances are categorized according to their aggregate consump

tion over a year (Figure 10). Based on statistical data [16] and considering the total house

hold consumption over the year, the average consumption during the day of each appliancegroup can be computed. In order to quantify the potential of the HLS scheme, the specific

utilization factors of each appliance group have to be defined. For this purpose, typical

utilization patterns of each appliance group are considered. The specific utilization fac

tors are, thus, derived from the normalization of the instantaneous consumption of each

appliance group with its average consumption over the day.

TV- HiFi

Refrigerators-FreezersWashing

7%

22%12%

arm-waterboilers

14%Small electric

devices23%

ElectricHeating

3%

Lighting9%

Cookingappliances

10%

Figure 10: Share of consumption of the household appliances [5].

The specific consumption of each appliance group, which equals to the product of the

normalized utilization and the average consumption, describes the household consumption

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of each appliance group during the day, including both the vital and non vital loads

(Figure 11).

40

50

60

70

80

Load[G

W]

Small devices

TV-Hifi

Cooking devices

Lighting

Washing and

drying devicesElectric heating

Warm-water boiler

0

10

20

30

0:00

0:45

1:30

2:15

3:00

3:45

4:30

5:15

6:00

6:45

7:30

8:15

9:00

9:45

10:30

11:15

12:00

12:45

13:30

14:15

15:00

15:45

16:30

17:15

18:00

18:45

19:30

20:15

21:00

21:45

22:30

23:15

Time of the day

Refrigerator-Freezer

Total German loadprofile

Figure 11: Power consumption of each household appliance group over the day.

The groups that include thermal appliances are considered to be nonvital due to their

high inertia which makes the interruption of their power supply hardly observed by the

consumers. Such appliances are the refrigerators, the freezers, the warmwater boilers and

the electric heating. It is assumed that this group of appliances offers control reserves

during the day, constituting the base load 4. Therefore, refrigerators, freezers and boilers are

assumed to have constant utilization during the day and, therefore, provide a constant base

household load for the HLS scheme. However, the utilization of the rest of the appliance

groups varies during the day, shaping the household load profile curve and significantly

4Warmwater boilers power consumption is often shifted to the night due to special tariffs. However, in

the present study, the are assumed to participate in a load control scheme and have constant consumption

over the day.

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differentiating the household load during the day. The base household load over the whole

day is approximately 8.5 GW, while the household load peak can be found during the

evening hours and is in the order of 30 GW.

The potential of the HLS scheme is perceived as the total sheddable household load at

each time instant, considering only the nonvital devices and their respective consumption.

The nonvital devices, i.e. the sheddable devices, are prioritized using as a criterion their

comfort loss. Comfort loss can be defined as an indicator for assessing the degree of the

annoyance caused to the consumers by shedding a specific appliance group. Appliances are

characterized by their comfort loss representing the extent to which their disconnection

is observed by the consumers. The comfort loss is not considered to be uniform for each

device over the day or over the year, but varies according to the utilization and necessity.

4.2 The potential of UnderFrequency Household

Load Shedding

In the previous Section 4.1, the sheddable household load has been defined as the non

vital devices within a household. Additionally, each device has been attributed with a

factor indicating its individual comfort loss. Since the goal is to develop a simple, flexible

and fast mechanism for the decentralized HLS scheme, the nonvital devices are further

categorized. Each category is characterized by a single value of comfort loss (Table 5).

However, each category does not have constant comfort loss over the day and over the

year, since there are significant variations of the lifestyle and the weather conditions.

The thermal appliances together with the battery chargers represent the category with

the lowest comfort loss, and thus, the first appliance category to be shed. The washingappliances, including the washing machine, the dishwasher and the dryer, are also of

constant and relatively low comfort loss during the day and during the year, representing

the second category to be shed. Electric heating is not in operation during the summer,

and therefore, its contribution to the available sheddable load is zero during the summer.

However, during the winter the utilization of electric heating is assumed to be constant

over the day.

The comfort loss of the lights is higher during the night and during the winter than during

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Appliances Categories Comfort Loss

0:00 5.30 5.30 15:00 14:30 20:00 20:00 24:00

Refrigerator Freezer

1 1 1 1Warm water boilerElectrical heating

Battery charger

Lights 6 3 3 4

Microwave Oven

4 5 4 3Oven

Coffee Machine

Iron

1 4 5 5Vacuum MachineHair Dryer

Washing Machine

2 2 2 2Dryer

Dishwasher

TV

5 6 6 6DVD

HiFi

Table 5: Comfort loss of each appliance category.

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the day and summer, respectively. The cooking appliances, including the microwave oven,

the electric oven and the coffeemachine, are mainly switched on during the morning and

early evening hours. Therefore, their utilization as well as their comfort loss is increased

during these hours. The small electric devices represent the nonvital load, such as the iron,

the vacuum cleaner and the hairdryer. Their comfort loss is highly dependent on their

utilization which is assumed to be higher during the evening. The most critical appliance

category includes the devices whose shedding is immediately realized by the consumers,

such as TV, DVD and HiFi, and may cause annoyance to the users. Their utilization and,

consequently, their comfort loss is high during the evening and before midnight, making

them the last load to be shed during the day, whereas their utilization is high during the

evening and before midnight.

The comfort loss indicators of most of the appliance categories vary during the day, since

their utilization and necessity also vary. Therefore, the shedding order of these appliance

categories should change according to their comfort loss. The comfort loss indicators de

termine the shedding order of the appliances categories at each time instant. Since the

main target of the HLS is the stabilization of the system in case of a disturbance with the

minimum comfort loss to the consumers and HLS is a decentralized scheme, it is necessary

that the shedding order of the appliance categories is updated automatically. It is assumed

that the data concerning the available sheddable load of each category and the shedding

order of the appliances are updated four times per day, representing roughly the changes

of the comfort loss values.

Based on the previous assumptions and on the instantaneous consumption of each appliance

group, the potential of the HLS scheme considering the total sheddable household load of

Germany, i.e. 39700000 households, during the day can be computed. Considering also the

shedding order of the appliance categories, the percentage of the total German load to be

shed at each step of the HLS scheme provides an indicator of the efficiency of the scheme

during a disturbance in the power system (Figure 12). The numbering of the categories

order to be shed corresponds to the value of the comfort loss for each appliance category.

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20,00%

25,00%

30,00%

35,00%

40,00%

45,00%Category 6

Category 5

Category 4

Category 3

Category 2

Category 1

otal share ofGerman load

0,00%

5,00%

10,00%

15,00%

20,00%

25,00%

30,00%

35,00%

40,00%

45,00%

0:00

1:00

2:00

3:00

4:00

5:00

6:00

7:00

8:00

9:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

Category 6

Category 5

Category 4

Category 3

Category 2

Category 1

otal share ofGerman load

Figure 12: Sheddable household load in Germany.

The base household load consisting of the thermal appliances and the battery chargers

constitutes during the day the first household loads to be shed, providing for the HLS

scheme a potential of almost 10% of the total German load. Due to the varying utilization,

functionality and comfort loss indicators of the rest of the appliance categories, the total

available sheddable household load in Germany is not constant during the day, but ranges

from 12% to 35% of the total German load.

The HLS scheme can be implemented either for prevention of the triggering of the CLS or

for complete substitution of CLS. The potential of the HLS scheme depends in both cases

on the time of the day, i.e. the load conditions, whereas the applied mechanism and the

demands for the available sheddable load of each function differ. By implementing the HLS

scheme as a complement to CLS, the main target is to delay or even prevent the triggering

of CLS by shedding individual household loads before the frequency drops to the predefined

thresholds of CLS. In this case, the number of German households considered determine

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the potential of the scheme.

In order to assess the potential of the HLS scheme at the time frames for which a completeset of data is available, the total sheddable load within a German household should be

quantified for 3 a.m. and 11 a.m. on a winter and on a summer day (Table 4.2). As

expected, during the night the available sheddable load is significantly lower, while it is

slightly differentiated between winter and summer days.

Electrical devices

Available Sheddable load

per Household (in W)

Winter Summer

11 a.m 3 a.m 11 a.m 3 a.m

Refrigerator 105.738 105.738 105.738 105.738

Warm water boiler 62.288 62.288 62.288 62.288

Electrical Heating 1.142 1.142 0.000 0.000

Battery charger 9.803 1.634 9.803 1.634

Nonvital lights 4.949 1.252 4.949 1.252

Microwave Oven 25.000 0.000 25.000 0.000

Oven 100.001 0.000 100.001 0.000

Coffee Machine 19.606 3.268 19.606 3.268Iron 14.705 2.451 14.705 2.451

Vacuum Machine 19.606 3.268 19.606 3.268

Hair Dryer 19.606 3.268 19.606 3.268

Washing Machine 38.346 0.000 38.346 0.000

Dryer 30.677 0.000 30.677 0.000

Dishwasher 20.707 0.000 20.707 0.000

TV 4.129 0.000 4.129 0.000

DVD 1.032 0.000 1.032 0.000AudioHiFi 2.064 0.000 2.064 0.000

Table 6: Sheddable load per German household.

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4.3 UnderFrequency Household Load Shedding as a

complement to Conventional Load SheddingThe HLS scheme as a complement to the CLS is triggered at thresholds higher than those

defined for the CLS. The goal is to delay or preferably prevent the triggering of CLS, thus

minimizing the costs related to the disturbance and the comfort loss to the consumers.

There are six frequency thresholds defined, corresponding to the six levels of comfort loss

(Figure 13). Taking into account the tolerance for the frequency deviation from its nominal

value of 50 Hz and in an attempt to prevent the unnecessary triggering of the HLS, the

first frequency threshold is set to 49.8 Hz. The frequency threshold for the CLS is set bythe UCTE to 49 Hz. Thus, the frequency steps for the HLS are set to 0.1 Hz, i.e. the range

49.849.3 Hz.

Figure 13: HLS scheme.

4.3.1 Frequency response model

The HLS scheme is implemented complementary to the CLS mechanism in order to delay

or even prevent the complete loss of load in certain areas under emergency conditions.

Therefore, the performance of the HLS scheme as a complement to the CLS mechanism

can be quantified by additionally including in the frequency response model of the inter

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connected system the block describing the function of the HLS mechanism (Figure 14).

The input to the HLS block is the frequency deviation from its nominal value. When the

system frequency drops to the predefined thresholds, the HLS mechanism is triggered and

the respective household load category is disconnected (Figure 15). The lookup table cor

responds the number of HLS stages being triggered to the cumulative household load that

has to be shed. Since the system frequency is sampled in variable steps, a set of flip flops is

implemented in order to avoid the multiple consideration of each household category that

is shed (Figure 16).

1

0

f0

Turbine dynamics

1

7s+1

System inertia

f0/(2*H*S)

Sum of f0+df

Sum of

loads of 24 UCTE countries

SaturationPrimary control

-1/(Spr*f0/S)

Net Import

Load

Load

1

s

Households Load Shedding

dfHousehold Load shed

Generation

Frequency Dependency of Loads

1.66*S/f0

Final f

freq

Distributed

Generation

DG

Conventional

Load Shedding

dfLoad shed

Figure 14: Frequency response model including the HLS mechanism.

The coordination of the two load shedding schemes, i.e. the CLS and the HLS, is crucial for

the stability of the system when the CLS is triggered. The degree of correlation of the two

load shedding schemes significantly depends on the number of households participating in

the HLS scheme and the plan according to which feeders are shed for the CLS. The main

point of interest is the assessment of the performance of the HLS, since the CLS is already

implemented and welldefined. Therefore, it is assumed that once the CLS is not prevented,

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it acts completely independently from the HLS by shedding the predefined share of total

load, whereas the HLS acts until the CLS is triggered.

HouseholdLoad Shed

1

Subtract

Lookup Table

In1 Out1

In1 Out1

In1 Out1

In1 Out1

In1 Out1

In1 Out1

-0.8

-0.6

-0.8

-0.5

-0.8

-0.4

-0.8

-0.2

-0.8

-0.7

-0.8

-0.3

6th stage

upulo

5th stage

upulo

4th stage

upulo

3rd stage

upulo

2nd stage

upulo

1st stage

upulo

df

1

Figure 15: HLS mechanism.

Out1

1

S

R

Q

!Q

S

R

Q

!Q Logical

Operator

OR

Detect

Decrease

U < U/z

Data Type Conversion

boolean

0

In1

1

Figure 16: Set of flip flops.

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4.4 UnderFrequency Household Load Shedding for

substitution of Conventional Load SheddingThe HLS scheme can be alternatively implemented for substitution of the CLS scheme.

The goal is to completely substitute the function of the CLS with the HLS scheme while

being compliant with the UCTE guidelines regarding the emergency measures. Therefore,

the frequency thresholds for the HLS scheme as a substitution of the CLS are set equal

to those of the CLS, whereas at each frequency threshold the household load to be shed

should equal to 10% of the total German load.

The category with the lowest comfort loss, i.e. the refrigerators, boilers and electric heating,can successfully fulfill the UCTE requirements for the first load shedding step, assuming

the participation of 100% of the German households (39 million) in the HLS scheme.

For the subsequent load shedding steps, the shedding order of the devices categories is

maintained. Thus, the devices categories are grouped together, so as the sheddable load

at each shedding step amounts at least to 10% of the total German load. In the case that

the sheddable household load is insufficient to cover 10% of the total German load for

the second and third load shedding stages, the household loads are grouped in a way to

amount to the maximum available load. Of interest in the present study is the capability ofthe Household Load Shedding scheme to completely substitute the existing load shedding

schemes.

4.4.1 Frequency Response Model

The performance of the HLS scheme for the complete substitution of the CLS can be

described by completely substituting the CLS block by the HLS block in the frequency

response of the UCTE power system (Figure 17). The contribution of the DG to the totalgeneration of the UCTE is considered, whereas the additional loss of generation due to loss

of DG is avoided, since feeders are not shed.

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Household

Load shed

1

Lookup Table

In1 Out1

In1 Out1

In1 Out1

-1.6

-1

-1.6

-1.3

3rd stage


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I. Stefanidou & M. Zerva 5. Reference Cases Results

5 Reference Cases Results

The purpose of the frequency control mechanisms of the power system is to maintain the

power balance between the generation and consumption and, thus, guarantee the reliability

and the security of the system. Deregulation of the electricity market has boosted the

international trade of electricity and, therefore, has forced the interconnected power system

to operate closer to its limits. The tripping of a generator, the tripping of a transmission

line or the sudden increase of the load may result in the decrease of the frequency from

its nominal value. In case of lack of generation, the frequency drops from its nominal

value and all member countries of the UCTE follow certain procedures defined in the

UCTE Operation Handbook, so as to stabilize the system and prevent the spreading of

the disturbance.

Figure 19: Physical and planned flows within the UCTE [6].

Under normal conditions, the crossborder exchanges vary significantly according to time,

weather conditions and locality. Tielines which were initially built for emergency and aux

iliary purposes are used nowadays for trading. For the protection and the security of the

system, the traded quantities and the power flows are planned and the stability of the

system is tested ahead by simulation. However, the physical flows may differ from the

planned ones, further stressing the system and making it more vulnerable to imminent

disturbances (Figure 19). Considering the fact that limited capacity mainly exists for the

interconnections of the control zones rather than for the transmissions system within a

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control zone, the study cases include the outage of the interconnection lines and, subse

quently, the islanding of areas. Therefore, in order to artificially create disturbances within

the UCTE power system, the loadgeneration balance is affected either by the outage of

interconnection lines or by the outage of generators.

5.1 Reference Cases

In the context of this study, the effects of the Distributed Generation present in the systemand the effectiveness of the conventional and the household load shedding are evaluated

through two study cases. In both cases, the disturbance is a lack of generation due to

the islanding of parts of the UCTE system. Individual control zones are kept intact, i.e.

there is no tripping of transmission lines within the control zones. The lack of generation

is attributed to the loss of interconnection lines, i.e. loss of net import and probably also

generation loss, since a major disturbance is mainly caused by the cumulative impact of

such incidents. The set of data available by the UCTE limits the appropriate time snapshots

for which the power system frequency response can be evaluated at 3 a.m. and at 11 a.m.For completeness reasons, the cases are evaluated for different seasons of the year, so as to

represent the different weather conditions and subsequently the different household load

and Distributed Generation values.

5.1.1 Summer scenario

The summer day scenario includes the islanding of four countries, i.e. Germany, Switzer

land, Austria and Italy and the additional loss of 12 GW of generation within Italy (Fig

ure 20). The data used concern the 16th of July 2008, for which the UCTE load peaks

during the summer and sufficient published data are available. Under the emergency con

ditions, where interconnections to all other UCTE member countries, as well as the DC

link to the Nordic countries, are lost, the power deficit at 11 a.m. is 14561 MW, while at

3 a.m. the power deficit of the islanded system is 17748 MW.

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Figure 21: Winter scenario.

5.2 Simulation Results

The frequency response of the power system to the disturbance reference cases is simulated

in the environment of MATLAB with the toolbox SIMULINK. The derived model for

the interconnected system of UCTE (see Section) is such that no time delay at the load

shedding stages across the UCTE member countries is assumed. The data concerning the

potential of DG and the household load of Germany and the UCTE published data of the

system net import and load are used as inputs to the model.

5.2.1 Case 1 Summer scenario, 11 a.m.

The first case considered represents the summer scenario at 11 a.m. The data used as inputs

to the frequency response model in order for the first case to be simulated are presented

at the following Table 7.

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0 5 10 15 20 25 30 35 40

48.8

49

49.2

49.4

49.6

49.8

50

50.2

Time [sec]

Frequency

[Hz

]

2008, 7.11% from DG2010 BEE e.V, 10.43% from DG

2020 BEE e.V, 31% from DG

2010 Leits., 9.67% from DG


No DG installations considered

Figure 22: Case 1 Dynamic response including DG.

0 5 10 15 20 25 30 35 4049

49.1

49.2

49.3

49.4

49.5

49.6

49.7

49.8

49.9

50

Time [sec]

Frequency

[Hz

]

CLS with DG considered

10% HLS participation





Figure 23: Case 1 Dynamic response with different household participations.

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0 10 20 30 4049.2

49.4

49.6

49.8

50

Time [sec]

Frequency

[Hz]

70% Participation of Households

0 10 20 30 4049.5

49.6

49.7

49.8

49.9

50


Time [sec]

Frequency

[Hz]

0 10 20 30 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

0 10 20 30 40

20

10

0

10

20

Time [sec]

Pow

er

[GW]

dPCLSHLS

dPCLSHLS

Figure 26: Case 1 Dynamic response with 70% and 100% of the German households

participating in the HLS scheme.

0 5 10 15 20 25 30 35 4049

49.2

49.4

49.6

49.8

50

50.2

50.4

Time [sec]

Frequency

[Hz

]

CLS without considering DGCLS considering DGHLS

Figure 27: Case 1 Dynamic response with HLS scheme substituting the CLS mechanism

for Germany.

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0 5 10 15 20 25 30 35 4049.5

49.6

49.7

49.8

49.9

50

Time [sec]

Frequency

[Hz]

0 5 10 15 20 25 30 35 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

HLS

dP

Figure 28: Case 1 Dynamic response with HLS scheme substituting the CLS mechanism

for Germany.

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5.2.2 Case 2 Summer scenario, 3 a.m.

The second case studied represent the summer scenario at 3 a.m. The set of input data to

the frequency response model for the second case are given in the following Table 8.

Generation 74429 MW

Load 92177 MW

Net import 0 MW

Power deficit 17748 MW

Sheddable load per household 188.17 W

DG installed capacity 2008 6607.82 MWDG 2010 BEE e.V. 8126.16 MW

DG 2020 BEE e.V. 15570.84 MW

DG 2010 Leitszenario 2008 7680.53 MW


Table 8: Case 2 Power data.

The power deficit of 17.75 GW is compensated by the activation of two underfrequency

load shedding stages, i.e. the frequency decay is intercepted at 48.7 Hz. Distributed Gen

eration represents 8.88% of the total generation, with this share rising up to 20.92% in the

future penetration scenarios (Figure 29).

The activation effect of the HLS mechanism can be observed due to the small delay of

the triggering of the two required stages of the CLS (Figure 30. However, the large power

deficit combined with the low household load during the night limits the effectiveness of

the HLS. Therefore, the triggering of the CLS is not avoided even under the favorable

conditions of 100% of households participation (Figures 31, 32, 33).

In the case of the complete substitution of the CLS by the HLS the sheddable household

load is insufficient for covering the UCTEcompliant second load shedding stage (20% of

the total German load). The inability of the HLS scheme to cover the second load shedding

step during the night was expected according to the quantified sheddable load potential

which does not exceed the 15% of the total German load (Figures 34, 35).

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0 5 10 15 20 25 30 35 4048.6

48.8

49

49.2

49.4

49.6

49.8

50

50.2

50.4

Time [sec]

Frequency

[Hz

]

2008, 8.88% from DG

2010 BEE e.V, 10.92% from DG2020 BEE e.V, 20.92% from DG


2020, Leits., 20% from DG



0 5 10 15 20 25 30 35 4048.6

48.8

49

49.2

49.4

49.6

49.8

50

Time [sec]

Frequency

[Hz

]







Figure 30: Case 2 Dynamic response with different household participation.

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0 10 20 30 4048.5

49

49.5

50

Time [sec]

Frequency

[Hz]

Without HLS

0 10 20 30 4048.5

49

49.5

50


Time [sec]

Frequency

[Hz]

0 10 20 30 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

0 10 20 30 40

20

10

0

10

20

Time [sec]

Pow

er

[GW]

dPCLSHLS

dPCLSHLS

Figure 31: Case 2 Dynamic response without the HLS mechanism and with the partici

pation of 10% of the German households.

0 10 20 30 4048.5

49

49.5

50

Time [sec]

Frequency

[Hz]


0 10 20 30 4048.5

49

49.5


Time [sec]

Frequency

[Hz]

0 10 20 30 4020

10

0

10

20

Time [sec]

Power

[GW

]

0 10 20 30 40

20

10

0

10

20

Time [sec]

Power

[GW

]

dPCLSHLS

dPCLSHLS



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0 10 20 30 4048.5

49

49.5

50

Time [sec]

Frequency

[Hz]


0 10 20 30 4048.5

49

49.5

50


Time [sec]

Frequency

[Hz]

0 10 20 30 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

0 10 20 30 40

20

10

0

10

20

Time [sec]

Pow

er

[GW]

dPCLSHLS

dPCLSHLS



0 5 10 15 20 25 30 35 4048.6

48.8

49

49.2

49.4

49.6

49.8

50

50.2

50.4

Time [sec]

Frequency

[Hz

]


Figure 34: Case 2 Dynamic response with the HLS scheme substituting the CLS mecha

nism for Germany.

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0 5 10 15 20 25 30 35 4048.5

49

49.5

50

Time [sec]

Frequency

[Hz]

0 5 10 15 20 25 30 35 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

HLSdP


nism for Germany.

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5.2.3 Case 3 Winter scenario, 11 a.m.

The input data to the frequency response model in the third case, representing the winter

scenario at 11 a.m. are shown in the following Table 9.

Generation 210557 MW

Load 221883 MW

Net import 30 MW




DG 2020 BEE e.V. 27620.6 MW




The system under study of the second scenario is larger and therefore more robust. The

power deficit of 11.3 GW is compensated with the activation of the first underfrequency

load shedding stage. The contribution of the Distributed Generation is significantly smaller

(4.16%) and thus, the negative effects of the additional loss of generation due to load

shedding are less observable (Figure 36).

The household load of the 30% of the German households proves to be sufficient to cover

the power deficit of the system under study, without shedding the category with the highest

comfort loss. The 50% of the German households have a total sheddable load enough to

stabilize the system frequency with only four HLS stages triggered (Figures 37, 38, 39, 40).

The HLS mechanism functioning as a substitution of the CLS proves to be successful in

eliminating the disturbance caused on a winter day (Figures 41, 42). The overshedding of

the HLS mechanism compared to the CLS is owned up to the fact that the household load

in Germany is categorized in six categories. The categories are grouped together at each

stage in order to amount to at least 10% of the total German load and they cannot be

further split, since the decentralized HLS mechanism is preset.

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0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[Hz

]

2008, 4.16% from DG

2010 BEE e.V., 5.52% from DG2020 BEE e.V., 13.12% from DG





0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[Hz

]








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0 10 20 30 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[H

z]

Without HLS

0 10 20 30 4049

49.5

50

50.5

51

51.5


Time [sec]

Frequency

[H

z]

0 10 20 30 4030

20

10

0

10

20

Time [sec]

Pow

er

[GW]

0 10 20 30 40

30

20

10

0

10

20

Time [sec]

Pow

er

[GW]

dP

CLS

HLS

dP

CLS

HLS



0 10 20 30 4049.2

49.4

49.6

49.8

50

Time [sec]

Frequency

[Hz]


0 10 20 30 4049.5

49.6

49.7

49.8

49.9


Time [sec]

Frequency

[Hz]

0 10 20 30 4015

10

5

0

5

10

Time [sec]

Power

[GW

]

0 10 20 30 40

15

10

5

0

5

10

Time [sec]

Power

[GW

]

dPCLSHLS dPCLSHLS



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0 10 20 30 4049.6

49.7

49.8

49.9

50

Time [sec]

Frequency

[Hz]


0 10 20 30 4049.7

49.8

49.9

50

50.1


Time [sec]

Frequency

[H

z]

0 10 20 30 4015

10

5

0

5

10

Time [sec]

Pow

er

[GW]

0 10 20 30 40

20

10

0

10

20

Time [sec]

Pow

er

[GW]

dPCLSHLS

dPCLSHLS



0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

52

Time [sec]

Frequency

[Hz

]



nism for Germany.

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0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

52

Time [sec]

Frequency

[H

z]

0 5 10 15 20 25 30 35 4020

10

0

10

20

30

Time [sec]

Power

[GW]

HLS

dP


nism for Germany.

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5.2.4 Case 4 Winter scenario, 3 a.m.

The input data to the frequency response model in the fourth case, representing the winter

scenario at 3 a.m. are shown in the following Table 10.

Generation 153942 MW

Load 160818 MW

Net import 321 MW




DG 2020 BEE e.V. 18779 MW




The frequency drop is eliminated at 49 Hz, i.e. the first underfrequency load shedding

stage is triggered. The power deficit of 7.2 GW is fully compensated, without, however,

achieving to avoid load overshedding (Figure 43).

The triggering of the CLS is completely avoided with the participation of 30% of the Ger

man households (Figures 44, 45, 46). With a participation of at least the 70% of the German

households in the HLS mechanism, the system frequency is stabilized only by disconnecting

the first HLS category, with the lowest comfort loss to the consumers (Figure 47).

On a winter day, during night, the substitutional function of the HLS mechanism proves to

be successful in stabilizing the system (Figures 48, 49, in spite the fact that the sheddable

household load is limited including mainly the first category with the appliances with

high inertia. Thus, the household load mechanism proves to be compliant with the UCTE

guidelines and sufficient for covering the first shedding stage at all times.

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0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[Hz

]

2008, 5.14% from DG

2010 BEE e.V, 6.34% from DG2020 BEE e.V, 12.2% from DG





0 5 10 15 20 25 30 35 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[Hz

]








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0 10 20 30 4049

49.5

50

50.5

51

51.5

Time [sec]

Frequency

[Hz]

Without HLS

0 10 20 30 4049

49.5

50

50.5

51

51.5


Time [sec]

Frequency

[Hz]

0 10 20 30 4020

10

0

10

20

Time [sec]

Pow

er

[GW]

0 10 20 30 40

10

0

10

20

10

20

10

Time [sec]

Pow

er

[GW]

dPCLSHLS

dPCLSHLS



0 10 20 30 4049.2

49.4

49.6

49.8

50

Time [sec]

Frequency

[Hz]


0 10 20 30 4049.5

49.6

49.7

49.8

49.9


Time [sec]

Frequency

[Hz]

0 10 20 30 4010

0

10

20

Time [sec]

Power

[GW

]

0 10 20 30 4010

0

Documents

Control Strategies for Under-Frequency Load Shedding