1

KEY ENERGY MANAGEMENT ISSUES OF SETTING MARKET CLEARING PRICE

(MCP) IN MICRO-GRID SCENARIO

A.K.Basu

(1) , T.K.Panigrahi

(1) , S.Chowdhury

(2) , S.P.Chowdhury

(1) , N.Chakraborty

(1)

A.Sinha (3)

and Y.H.Song(4)

(1) Jadavpur University, India (2) Women’s Polytechnic, India (3) Tata Consultancy Services Ltd., India

(4) Liverpool University, UK

ABSTRACT

Micro grid is an epitome of a macro grid but works in low voltage comprising of various small-distributed energy

resources (DERs), energy storage devices, and controllable loads being interfaced through fast acting power electronic

devices. Combined heat and power (CHP) produced by DERs are utilized in the local market where Micro Grid

operates either in island mode or in grid-connected mode. The CHP mode of operation makes the Micro Grid most

efficient and economic. Like deregulation regime in Micro Grid market, multi agent generator providers may be

considered to make the Micro Grid market competitive. The reason for competitive electricity market is to serve the

consumers at a reduced price. The main purpose of this paper is to analyze and propose the pricing mechanism for

Micro Grid energy in the competitive electricity market. Central controller of the Micro Grid (µcc) is the main brain

behind all energy management system (EMS) activities, which includes participation in the bidding to settle market-

clearing price (MCP). Two important market settlement techniques – Day-ahead and Real-time – have been discussed

briefly in this paper. Uniform and Pay-as-bid pricing rules have been discussed separately for electricity pricing fixation

in the context of Micro Grid. In this paper marketing strategies of some of the renewable DERs – mainly Photovoltaic

(PV) and wind generator – have been considered. Wind power is now a potential candidate in non-conventional power

generation family. Power available from wind and PV system cost high and is of intermittent in nature. Participation of

these two renewable DERs along with Micro turbine, Diesel generator, fuel cells etc. in the bidding for market clearing

price (MCP) make the market complex. This paper gives a brief guideline for marketing of PV and wind power.

Consumers in the Micro Grid system are categorized as shed-able and non-shed-able according to their priority. How

these loads affect demand curve have also been discussed. This paper presents a case study on price determination

based on demand and supply side bidding strategies. The impacts of congestion management, market power, carbon

taxation, price volatility, etc. on pricing have also been discussed in the context of Micro Grid.

Keywords: Energy Management, Market, Microgrid, Distributed Energy Resources (DERs), Market Clearing Price

1 INTRODUCTION

Electric power system – all the three sections –

Generation, Transmission, and Distribution – is

ushering a progressive transition from a centralized

control to distributed control regime.

Micro-Grid is a concept where local energy

potentials, both in renewable (such as small wind, PV,

etc.) and non-conventional (micro-turbine, Fuel cells,

Diesel generator) resources, are tapped and

interconnected among themselves as well as with LV

Macro-Grid. These small DERs have different owners.

They take decisions – scheduling of generation as per

load forecast (i.e., unit commitment) and Economic

dispatch of loads – locally with the help of local

controllers (µc) connected with each DER and Micro-

Grid Central Controller (µ cc). In the islanding operation

of Micro-Grid, each source caters only those loads,

which are stipulated for the source. (3, 9)

But when these

sources are grid-connected, which is most desirable,

then the action of the controllers (both µ c and µ cc)

should have a certain degree of intelligence for

participation in the common and competitive market.

The purpose of the Energy Management System

(EMS) in the Micro-Grid scenario is to make decisions

regarding the best use of the generator for producing

electric power and heat i.e. combined heat and power

(CHP) operation. (3)

Such decisions will be based upon

the heat requirements of the local establishments, the

climate, the price of electric power, the cost of fuel and

many other considerations. Micro-Source central

controller (µ cc) acts as a main operator to take decisions

regarding the supply of CHP services to be provided as

per demand. Like deregulated regime in the Macro-

Grid, multi-agent generating providers are considered in

the Micro-Grid system. The main idea of this paper is to

determine the market clearing price (MCP) due to

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dispatch of an aggregated group of different kinds of

DERs and an aggregated group of different kinds of

consumers. These consumers are categorized as

controllable loads i.e., which can be shed and

uninterruptible loads.

An electricity market is a system for effecting the

purchase and sale of electricity using supply and

demand to set the price.(1)

Reducing the price paid by

consumers for electricity is invariably the first reason

given for introducing competitive electricity markets.

Micro-Grid operates in a local market and usually cater

to the customers of medium sizes (such as, commercial

complex, small industries etc.) and residential. These

customers do not have the financial incentives and the

expertise required to contribute effectively in the price

matter to such a complex local market. Possibly as a

consequence of this lack of representation, most

electricity markets do not treat consumers as a genuine

demand side capable of making rational decisions, but

simply as a load that needs to be served under all

conditions.(2)

Active participation in these markets by

demand side remains minimal. This paper has

considered an active participation of both supply and

demand side and thus shown a power-trading model as

in fig. 1.Two important market settlement techniques

are generally adopted in the electricity market –Day-

ahead and Real-time. The day-ahead energy market is

designed for market participants with the day-ahead

prices. After the day-ahead market bidding period

closes, the system operator calculates day-ahead market

clearing prices (MCP) based on bids, offers, and

schedules submitted based on least cost, security

constrained, unit commitment and makes the day-ahead

scheduling for each hour of the next operating day. The

real time market is designed to provide opportunities for

generators that are available but not selected in the day-

ahead scheduling, might alter their bids for use in the

real-time market, otherwise their original day-ahead

market bids remain in effect for the real-time energy

market.(1)

Figure 1 Proposed Micro-Grid market model commercial

structure

With the rising environmental concerns, the wind

and solar energies are better choice at present. The

benefits of grid-connected PV schemes may be seen as

expressing concern for the environment, energy credit

associated with reduction in fuel consumption and an

opportunity to participate and contribute into a new

technology[4]. PV and wind were viewed primarily as a

power source for remote applications far from a Macro-

Grid. With the development of inverters for grid-

connected applications, interest in grid-connected PV

and wind grew[6][7]. Today, due to these changes and

burgeoning Government incentive programs, grid-

connected solar and wind are the fastest growing market

for generation technology. For power systems with a

substantial natural gas component, wind and solar

actually provides a hedge against fluctuations and

spikes in gas costs. This paper also analyses and

proposes the pricing mechanism for wind and solar

integrated into the electricity market.

A good trading mechanism is a basic need for the

market, but due to oligopolistic nature of the electricity

market there are fair chances of having the market

power and market abuse, which reduce the market

efficiency.[5] This paper discusses a few aspects, such

as congestion management, carbon taxation, market

power, price volatility, etc. which affect the price.

2 BIDDING PROCEDURE

In oligopolistic market, several producers compete

to win a share of the market and bid against each other

to supply electricity to the consumers. In current

electricity markets, either a single side bidding (the

generator side) or a double side biding (both generator

side and consumer side) is adopted. No matter whether

it is single side bidding or double, the generator

providers do not know the current level of demand and

consumers do not know the available capacity of

generators. This causes the more complications and

uncertainties in bidding for both sellers and buyers in

the electricity market. Furthermore, electricity auction

markets may have more than one commodity being bid

for simultaneously, for example, real-time energy,

operating reserve, and other ancillary service products.

There are two options of bidding followed by

generator providers – (1) block-generation bidding, (2)

sealed bid auction. In the first one, the portion of the

load curve a supplier hopes to win depends on

production cost estimate, temporal considerations of

demand variations, unit commitment costs and other

commercial considerations. In the second case, suppliers

submit their competitive bid to the pool operator for the

supply of the load forecasted by the operator. Each

supplier’s objective is to maximize benefit and on the

other hand, pool operator uses a dispatch strategy that

minimizes customer’s burden.

Two types of bidding mechanism are in vogue in the

electricity market – (1) single side bidding where only

Generator

Provider

Bids &

Offer

Power

Exchange

Controlled

by µcc

MCP

Index

On-line

Bulletin

Board

Govt. Licensed

Representatives

Supply Side

Bidding

Demand

Side

Bidding

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generator providers participate; (2) double side bidding

where both generator providers and consumers

participate. This paper formulates both types in the

section (iv).

3 MARKET CLEARING PRICING RULES

There are three important pricing rules for

electricity auction, but only two of them are generally

used in real-time markets – (1) uniform or single price

market clearing rules and (2) discriminatory or pay-as-

bid market clearing rules. First one is very common in

electricity market. In this process, sellers would receive

the market-clearing price (MCP) for their electricity,

even if they bid less than that price and all consumers

would pay the MCP, even if they bid more than that

price. The theory behind such a biding system is that all

bids to sell electricity would be priced at the marginal

cost of that electricity. As per the second rule, every

participant with winning bid pays or is paid at the price

of his bid. In this system, bidding is made by guessing

the cut-off price, not on marginal cost. There is mistake

in guessing from observing the results of the hourly

bids, twenty-four a day. Some lower cost firms would

guess incorrectly and bid above the cut-off price. Thus,

some high cost firms would generate and lower cost

firms would remain idle. Cost of generation would,

therefore, be increased above the market clearing cost.

Pay-as-bid system could be expected to increase the

total cost of generating electricity and would therefore

be less efficient than uniform market clearing system.

With the introduction of deregulation in the power

sector, the implementation of the uniform pricing

system came as a natural choice, since it is believed to

offer to the bidders the incentives to reveal their true

cost.

4 FORMULATION OF MARKET CLEARING

PRICE

The market-clearing price is the lowest price

obtained at the point of intersection of aggregated

supply and demand curves. At this price both suppliers

of generation and customers are satisfied and would

provide enough electricity from accepted sales bids to

satisfy all the accepted purchase bids. The sales bids are

usually arranged from the lowest offer price to the

highest offer price, i.e., in the bottom-up order. Whereas

purchase bids are arranged from their highest offer price

to the lowest offer price, i.e., top-down order. At the

MCP, the total sales bids would be equal to the total

purchase bids.

In a market, both the supply and demand bids are

of the same type, i.e., either block or linear bids.

Authors have presented the detail analysis of market

clearing price (MCP) in the competitive market for

linear bid cases.

(a) SINGLE SIDE BID MARKET: In this market

supply companies participates in the bidding. And

demand of the consumers is considered as constant

whatever the market price is. Authors have considered a

market comprising of CHP generators (e.g., micro-

turbines, fuel cells, etc.), renewable generators (e.g.,

wind, solar), and diesel back-up generators. Diesel

generator is generally used as back up but for

comparison purpose it has been taken with the

mainstream generators.

Q1 (p) = KW generated by bidder-1 (say, micro-turbine)

at a price ‘p’ $/kWh = Q1elec + Q1Th

Where Q1elec is electrical KW generated by micro-

turbine and Q1Th is thermal load generated by micro-

turbine converted to equivalent electrical load, using

Joule’s constant.

1

1 )(sm

ppQ = ----------------------------------- (1)

Where 1sm is the slope of the linear supply curve

of bidder-1. Similarly,

2

2 )(sm

ppQ = ……………………………………. (2)

= Q2elec + Q2Th

Where Q2 (p) is KW generated by bidder-2 (say,

fuel cell) at a price ‘p’ $/kWh

Likewise, combined supply curve for ‘N’ bidders will

be

Q (p) = Q1 (p) + Q2 (p) +……… Up to N

=

1sm

p+

2sm

p + ………………

=P ∑=

N

j

msj

1

1 ………………………………… (3)

As demand is fixed at ‘D’ (say), therefore at the

market clearing price (p*),

Q (p*) = D

P*∑=

N

j

msj

1

1 = D

P*=

∑=

N

j sjm

D

1

1 …………………………… (4)

In the equation (4), it is assumed that bidders have

enough capacity of generation. If the capacity limit –

both minimum generation (Qmin) and maximum

generation (Qmax) – is specified then the combined

supply curve (3) can be represented as,

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Q (p) = p ∑=

N

j

msj

1

1 [U (Q - Qmin) – U (Q- Qmax)]…….. (5)

Where functions

U (Q - Qmin) = 1, When Q>= Qmin;

= 0, When Q< Qmin;

And U (Q - Qmax) = 1, when Q >= Qmax

= 0, when Q< Qmax

Equating (5) with the demand ‘D’, the market-

clearing price (p*) can be determined.

(b) DOUBLE SIDE BID MARKET: In this market, elasticity

of demand curve has been considered. Both supply side

and demand side bidding are taken into account for

determination of market clearing price (p*). Both linear

supply and demand variations with price have been

considered for analysis.

D (p) = combined demand at price ‘p’ $/kWh

obtained from bids of N numbers of consumers

participating in the market =∑=

N

j djm

p

1

0-

∑=

N

j djm

p

1

………………………….… (6)

Figure 2 Linear Demand and supply bid curves

Where P0 is the price axis intercept of demand curve

varies with type of consumers. If at a particular price

(p), D (p) is considered aggregated demand for all the

participating consumers, therefore

D (p) =∑=

N

j djm

p

1

0 - P∑

=

N

j djm1

1 -------------------- (7)

At the MCP (p*),

P*∑=

N

j sjm1

1=∑

=

N

j djm

p

1

0- P*∑

=

N

j djm1

1………………. (8)

P*=

∑

∑

=

=

+

N

j djsj

N

j dj

mm

m

p

1

1

0

11…………………………… (9)

5 STUDY- CASES

Authors have studied a Micro-Grid system

comprising of following DERs, as shown in Table 1.

For the sake of simplicity, only three types of

conventional DERs along with renewable sources (wind

and solar) have been considered to bid into the market.

Table 1

Generator

type

Ms,

$/kWh

Qgmax,

KW

Qgmin, KW Heat

rate,KJ

/kWh

Bidder 1

(Micro-

Turbine)

0.1056 30 Minimum

power for

satisfying

the thermal

load

12,186

Bidder 2

(Fuel cell)

0.1386 50 Do

9,480

Bidder 3

(Diesel

gen.)

0.063 60 0 ---

Bidder 4

(wind

gen.)

0.27 10 0 ---

Bidder 5

(solar PV)

0.4756 20 0 ---

As the number of DERs increases, combined

supply curve is to be obtained, as explained in section

(IV). In the study following bidding strategies have

been considered:

Case-1: Linear supply bid with fixed demand (i.e.,

single sided bid market)

Case-2: Linear supply bid with linear demand bid (i.e.,

double sided bid market)

CASE-1: In this case, a constant demand of 80 KW is

considered. Analysis is performed for the following

cases:

(a) First, renewable energy sources (RES) – i.e., wind

and solar – are considered non-available. Demand is

met only by the other three DERs. MCP is obtained

from the intersection of the cumulative supply curve of

bidders-1, -2, -3, and fixed demand line of 80 KW, as

shown in Fig.3.

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Figure 3 Individual & combined supply curves and

fixed demand line

As per Fig. 3, MCP = $2.5/kWh

Power supplied by each generator to meet the demand

of 80 KW is shown in Table 2.

Table 2

Bidder Generator

output, KW

Payment, $

1 (Micro-

Turbine)

24.0 60

2 (Fuel cell) 18.0 45

3 (Diesel

gen.)

48.0 120

Total 80.0 225

(b) Considering both RESes are available, their

combined generations are 30 KW. RESes are considered

not participating in the bidding process. Therefore, their

generation only reduces the bidders (i.e., -1, -2, -3) total

dispatch from 80 KW to 50 KW. It is being considered

that both wind and solar power are available in the

daytime.

The corresponding MCP is now $1.5 /kWh (as per

Fig. 3). Since MCP is reduced, it may not be possible to

recover the cost of RESes and also the excess cost

during the non-availability of RESes. Therefore the

MCP is to be kept fixed at $2.5/kWh, but output of

bidders would be reduced by ∆Qi

=

sjm

p∆………………………………………………………………………… (10)

as shown in Fig. 3.

(i) Impact of bidding of RESes: The generation of

wind and solar are uncertain. Output variation of wind

and solar as well as MCP with the different bidding

rates are shown in Fig. 4.

Figure. 4 MCP vs. Bid Rate & Output vs. Bid Rate

curves when demand is fixed

There are two situations shown in the Fig. 4 – (i)

Restricted RESes: If the RESes bid at zero, it will be

completely dispatched and MCP will be 1.5 $/kWh.

Restricted output from RESes is possible in micro-grid

system due to presence of storage.

(ii) Unrestricted RESes: The MCP with restricted

RESes (i.e., 30 KW) is same as MCP at the unrestricted

RESes at bidding rate of 1.0. Maximum and minimum

MCP can be found out by partial differentiation of

Equation (4) with respect to bidding rate (ms) and then

equating to zero. For various bidding rate (ms) varying

from 0 to 10, payments and output are shown in the

Table 3 for the following two options:

Option 1: with fixed RESes of 30 KW, MCP=1.5$/kWh

when ms <1

Option 2: When ms between 1 and 10, MCP calculated

with RESes and output of bidders –1, -2, -3, as adjusted

by Eq. (10) are shown in Table 3.

Table-3 Gen. Type Output

(KW)

Payments, $

option 1

Output, KW Payment

s, $

Option 2

ms <1 1<ms<10

Bidder 1 14 21 14 33.6

Bidder 2 12 18 12 28.8

Bidder 3 24 36 24 57.6

RESes 30 45 30 72

Total 80 120 80 192

CASE 2: Two consumers participating in the bidding

are considered and shown in Fig. 5.Bidding data of the

consumers are given in Table 4. Linear bid data for

demand has been considered.

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Table 4

Consumer Mdj,

($/kWh/KW)

Po, ($/kWh)

Bidder 1 0.041 6.0

Bidder 2 0.077 7.0

MCP is calculated from the intersection of supply

and demand curves and it is found out as

$3.4/kWh.Corresponding demand of individual

consumers is found out from Fig 5.

Figure 5 Supply (aggregated) & Demand (Individual

and aggregated) curves

Figure 6 MCP vs. Bid Rate & Output vs. Bid

Rate curves when demand is elastic

Demand of:- Bidder 1: 64 KW and bidder 2: 46 KW;

total demand = 110 KW.

Generator providers meet this demand by supplying as

per schedule shown in (Fig. 3 & Fig. 5):

Micro-Turbine –33 KW, Fuel cell –26 KW, and Diesel-

gen. – 51 KW; Total generation = 110 KW.

If wind and solar RESes do not participate in the biding

process, then their contribution of 30 KW will reduce

the MCP at $3 /kWh and consumption of the consumers

will increase to:

Bidder 1: 72KW and bidder 2: 52 KW; total demand =

124 KW.

From Fig. 5, when RESes supply 30 KW, then supply of

other three bidders will be as follows:

Bidder 1 (micro-turbine): 23 KW, bidder 2 (Fuel

cell): 29 KW and bidder 3 (Diesel-gen): 49; Total

generation = 101 KW.

From Figure 6, when bidding rate of RESes less

than 1.0, then there is no impact on the MCP with

restricted RESes of 30 KW. With the increase of

bidding rate MCP increases, but power dispatched from

RESes is less. Table 4 shows the payments at various

MCP and corresponding output.

Table 4 Generator:

supply side

payment

Without

RESes:

power

output

(KW)

Without

RESes:

payment (at

$3.4/kWh)

With

RESes:

power

output

(KW)

With

RESes:

Payment

(at $3

/kWh)

Bidder 1 33 112.2 23 69

Bidder 2 26 88.4 29 87

Bidder 3 51 173.4 49 147

RESes 0 - 30 90

Total

payment

110 374.0 131 393

Demand

side:

Bidder 1 64 217.6 76 228

Bidder 2 46 156.4 55 165

Total

payment

110 374.0 131 393

6 VARIOUS IMPACTS ON ELECTRICITY

MARKET

The bidding strategies, used by generating

companies with the goal of maximizing their own

profits, show various potential possibilities to exercise

market power. Market power is simply the power that

market participants hold to manipulate the market in

their own favor. Various reasons for the existence of

market power are transmission congestion, market

players, and market structure.

Congestion is common in the electricity

transmission system. Micro-Grid system itself helps

respite from macro-grid congestion. Due to congestion,

price of energy increases from one part to another.

Scheduling of energy production in the day-ahead

market will also help to mitigate transmission

congestion issues. A large company (i.e., a big market

player) can easily manipulate energy prices that are set

far from its marginal cost. In the micro-grid market both

conventional (micro-turbine, fuel cell) and RESes

participate. Due to inconsistence behavior of RESes, the

market structure and market rules are also important

causes for some kind of exercise of market power, such

as what pricing mechanism is implied – uniform price

or pay-as-bid. Chances of market volatility in the micro-

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grid market are almost absent. Though a perfect match

between power production and power demand is hardly

possible, still due to presence of the storage system this

gap can be mitigated easily. Carbon emission alerts us

every time to shift the nature of electricity generation

from the fossil fuel type to non-conventional (i.e.,

renewable) type. In this case, micro-grid system of

generation has an edge over the conventional type.

Carbon taxation will indirectly encourage the micro-grid

system.

7 CONCLUSION

This paper presents a comparative analysis of MCP at various combinations of non

This paper presents a comparative analysis of MCP at

various combinations of non-conventional (i.e., RESes)

and conventional energy sources. With the uncertain

availability of RESes, it becomes difficult to find out

actual MCP at which trading is to be done. For this

RESes have been considered, in one case, participating

in the market as and when available basis. Also a case

with storage system has been considered for smooth out

this uncertainty of generation and responsible

participation in the bidding. Though Government

subsidy on price and environment-friendly nature of

generation are the encouragement for the use of RESes,

still uncertain availability is the main difficulty in their

wide spread use. Proper and transparent trading practice

can make a win-win situation. This paper could guide

market researchers with an idea of micro-grid market

comprising of RESes.

8 REFERENCES

1. Yon-Hua Song, Xi-Fan Wang (Eds.), “Operation of

market-oriented power systems”, springer, 2003

2. D. Caves, K. Eakin et.al, “Mitigating price spikes in

wholesale markets through market-based pricing in

retail markets”, The Elect. J., vol. 13, n0.3, pp 13-

23, Apr. 2000.

3. J.D.Kueck, et.al. “Micro grid energy management

system”, CERTS, Jan.2003.

4. Martel, S. et.al. “Avoided cost benefits of pv on

diesel-electric grids”, 24th

IEEE pv specialties

conference proceedings, 1994, pp 1048-1053

5. A. Fabbri, et.al, “Assessment of the cost associated

with wind generation prediction errors in a

liberalized electricity markets”, IEEE Trans. on

power systems, vol. 20, no. 3, pp.1440-1446,

august.

6. G. N.Bathurst, et.al. “Trading wind generation in

short term energy market”; IEEE Trans. on power

systems, vol.17, no.3, pp782-789, Aug2002.

7. K.Khouzam, “Prospect of domestic grid connected

pv systems under existing tariff conditions” 26th

IEEE pvsc, Sept.30-oct.3, 1997

8. Chris Marnay, et.al, “Modeling of customer

adoption of distributed energy resources”, CERTS,

Aug.2001.

9. R.Lasseter, et.al, “Integration of distributed energy

resources, the CERTS micro grid concepts”,

CERTS, 2002.

AUTHOR'S ADDRESS

The first author can be contacted at

Electrical Engineering Department

CIEM, Kolkata, India

Email (ak_basu2004@yahoo.com)

(spchowdhury@theiet.org)

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