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A Look-Ahead Energy Management System (EMS) Framework for Microgrids
Xianyong Feng, PhD
Center for Electromechanics (CEM)
University of Texas at Austin
Nov. 28, 2016
1
Outline
• Introduction
• Motivation
• Microgrid Control Operation
• Microgrid EMS Problem Description
• Case Studies
• Performance Analysis
• Conclusion
2
Introduction
• DOE Microgrid Definition: A group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid. A microgrid can connect and disconnect from the grid to enable it to operate in both grid-connected or island-mode.
3
PV system
ES system
~
Distributed
Generator M
~
Microgrid
Communication
link
Central
controller
Local
controller
Local
controller
Local
controller
Local
controller
Distributed
Generator 1
s1s2s3s4s5s6
s7
s8
s9
PCC
Utility
Grid
...
Controllable
load 2Critical
load Controllable
load N
Controllable
load 1
Local
controller
Local
controller
Local
controller
Local
controller
...
PCC
controller
· Utility electricity price signal
· Weather forecast
Introduction
• MW-level Microgrid at CEM in The University of Texas at Austin
4
~ ~
~ ~
M ~D
480 V AC source
3-ph
AC breaker
480 V AC source
3-ph
AC
breaker
490 kVA
480 V/808 V
transformer
DC
disconnectorAC
breaker
Diode rectifier
3.2 MVA
DC
disconnector
DC cable
DC
disconnector
DC
disconnector
DC
disconnector
DC
disconnector
1 MVA motor
drive
2 MVA
motor
5 MW
dynamometer
DC
disconnector
1.2 MVA
480 V/808 V
transformer
1.2 MVA
controlled
rectifier
2 MW
DC chopper
1.3 MW
resistive load
1120 VDC
1120 VDC
Zone 1
Zone 2
DC bus 1
DC bus 2
Motivation
• High Penetration Renewable• Accommodate high penetration
intermittent DERs in future grid
• Energy Efficiency• Reduce grid operation cost
• Reduce emission
• Grid Reliability and Resilience • Improve grid stability
• Reliable fault ride-through
• Seamless mode transitions
5
Time (sec)
Frequency (Hz)
60larger inertia
smaller inertia
LP is the same
1f
2f
n
i i
L
H
fP
dt
fd
1
rated
2
Total inertia
Stability and Resilience
PV generation (partial cloud day) Wind generation (daily curves)
Renewable Intermittency
10 hrs.
Microgrid Control Operation
• Tertiary Control • Economics and efficiency
• System security
• Secondary Control• System-level stability
• Power sharing
• Primary Control• Local stability
• Equipment protection
6
Tertiary
control
Secondary control
Primary control
Information flow
Decision signals
Economic dispatch
Unit commitment
Optimal power flow
Voltage var control
Time frame: seconds to minutes
Real-time load management
Secondary load-frequency control
Secondary voltage control
Automatic generation control
Time frame: 100s milliseconds
Droop control
Protection
Time frame: milliseconds
Look-ahead energy
management system
(EMS)
Microgrid EMS Problem Description
• Objective • Enable economic and secure
steady-state operation
• Seamless integration with local controllers
• Constraints• Power balance
• DG ramp rate and capacity
• ESS state of charge
• Operational constraint (voltage, current, and freq.)
7…
Mixed Integer Linear Programming (MILP)
problem
Microgrid EMS Problem Description
• Challenges• How to improve the predictive
control accuracy
• How to reduce computational complexity
• How to minimize ESS charging and discharging cycles
• How to integrate realistic operational constraints in real time economic dispatch
• How to minimize load interruptions during outage
8
• Solutions• Plan DERs using most recent
load and renewable forecasts
• Decoupled look-ahead DER schedule and real-time ED/OPF
• Designed a virtual cost associated with ESS
• Optimal power flow and sensitivity-based method are integrated in the ED
• Designed an optimal planned outage function
Case Study
• A modified IEEE 34-node system• Maximum load: 1.8 MW
• Rated voltage: 24.9 kV
• 1 diesel, 2 micro-turbine, 1 wind, and 1 PV/solar generators
• 2 energy storage systems
9
DG name DG 1 - diesel DG 2 – MT1 DG3 – MT2
Location Bus 824 Bus 840 Bus 854
No load cost ($/hour) 4 3 5
Fuel cost ($/kWh) 0.22 0.085 0.085
Start-up cost ($) 10 10 10
Shut-down cost ($) 10 10 10
Pmax (kW) 360 270 450
Pmin (kW) 72 54 90
Qmax (kvar) 174 130 217
Qmin (kvar) 0 0 0
Ramp rate (%/min) 40 30 30
ES name ES1 ES2
Location Bus 850 Bus 858
Maximum charging rate (kW) -20 -40
Maximum discharging rate (kW) 100 200
Maximum energy capacity (kWh) 200 600
Minimum energy capacity (kWh) 80 210
Charging efficiency (%) 80 85
Discharging efficiency (%) 85 90
Name Wind Solar
Location Bus 808 Bus 848
Capacity (kW) 200/400 100/200
Control type Continuous or discrete Continuous or discrete
Case Study
• Real-time simulator• Simulated the 34-node system
• Local controllers communicate with Opal-RT simulators
• Look-ahead microgrid EMS• Implemented on central
controller
• Dispatch signals are transferred to local controllers through LAN
10
Simulated 1.8 MW microgrid
Ethernet RT simulator
User interface
Local controllers for DERs
…
…
Local Area Network (LAN)
Central controller
Look-ahead microgrid
EMS
Measurement Control…
Hardware-in-the-loop test platform
Case Study
• Case 1: One-day look-ahead EMS in grid-connected mode operation with an outage• 2-step price signal
• A planned outage (4 am - 8 am)
• ESSs discharge to avoid using diesel generator (a higher-cost unit)
• ESSs charge before planned outage happens
• The ESS charge/discharge cycle is minimized
11
Diesel
MT 1MT 2
Case Study
• Case 2: One-day look-ahead EMS in island mode operation• ESSs discharge to avoid using
diesel generator (a higher-cost unit)
• ESSs charge before load is increased
• The ESS charge/discharge cycle is minimized
• Renewable energy is fully utilized
12
0 5 10 15 200
20
40
60
80
100
120
140
160
180
200
time (hour)
Win
d P
ow
er
(kW
)
0 5 10 15 200
20
40
60
80
100
120
time (hour)
Sola
r P
ow
er
(kW
)
0 5 10 15 200
200
400
600
800
1000
1200
1400
1600
1800
2000
time (hour)
Load D
em
and (
kW
)
0 5 10 15 200
50
100
150
200
250
300
350
400
450
500
time (hour)
Genera
tion P
ow
er
(kW
)
DG1
DG2
DG3
0 5 10 15 20-40
-20
0
20
40
60
80
100
120
time (hour)
ES
1 O
utp
ut P
ow
er
(kW
)
0 5 10 15 20-50
0
50
100
150
200
250
time (hour)
ES
2 O
utp
ut P
ow
er
(kW
)
Wind Power
Solar Power
Load Demand ESS2 Output Power
ESS1 Output Power
Generation Power
Diesel
MT 1
MT 2
Performance Analysis
• Performance Analysis• Each look-ahead DER
schedule problem (MILP problem) for the modified IEEE 34-node system with 7 DERs includes:• 1296 decision variables
• 2692 linear constraints
• The real-time ED/OPF is formulated as quadratic programming problem • The calculation can be finished
in 1 second on both platforms
13
Platform PC (Intel R Xeon E5606 2.13 GHz)
Embedded system (AM335x 1GHz ARM® Cortex-A8;
512MB RAM) Grid-connected
mode 9.8 sec 194 sec
Island mode 35.3 sec 554 sec
Performance of look-ahead DER schedule (averaged from 100 runs)
> 5 min
• A dedicated powerful computer is required to perform the central look-ahead EMS optimization in real time
Conclusion
• The look-ahead EMS approach fully utilizes the most recent load and renewable forecast to improve the predictive control accuracy
• The decoupled DER schedule and real-time ED approach significantly reduces the computational complexity
• The real-time OPF-based ED integrate operational constraints to generate realistic dispatch results
• The central EMS calculation can be accomplished in real time on a regular PC
14
Thank You
15