1
Real-Time Control of Distributed Energy
Resources
Y. Zhu, Senior Member, IEEE, K. Tomsovic, Fellow, IEEE
Abstract—Recently, there has been great interest in the
integration of Distributed Energy Resources (DER) at the
distribution level. DERs are potentially valuable providers of
ancillary services such as load following and contingency reserve
in distribution systems. This will require new control strategies
for coordinating their system performance. One issue that has
not been addressed sufficiently is the coordinated dispatch of
large numbers of DERs under normal operation or system
outage. In this paper, an AGC type control strategy is proposed
and implemented for the real time control of DERs. Simulation
results show that DERs are capable of providing load following
and contingency reserve services under the proportional control
mode or competitive control mode.
Index Terms—Ancillary services, Automatic Generation
Control, Competitive control, Contingency reserve, Distributed
energy resource, Distribution system, Load following,
Proportional control
R
I. INTRODUCTION
ECENT technology improvements in Distributed Energy
Resources (DERs) have provided the opportunity for
integration into distribution systems. With increasing power
demand, electric utility restructuring, and public
environmental policy, small DERs are in great need in order to
provide energy and ancillary services to satisfy on-site
customer needs. Among such DERs, microturbines and fuel
cells are promising due to their ability to operate with multiple
fuels, generally low emissions, high efficiency and high
reliability.
Slow dynamic models and load-following
capability have been developed and demonstrated in [1]. In
this paper, real-time control methodologies are developed for
microturbines and fuel cells.
A study indicates that up to 13% of the total power
generation is wasted in the form of line losses in distribution
systems [2]. Microturbines and fuel cells are good candidates
for providing energy locally due to their high efficiency and
reliability. This can greatly reduce losses at the distribution
level. Further with proper placement, losses at the
transmission level can be reduced and transmission congestion
can be eased [3].
By providing ancillary services, microturbines and fuel
Y. Zhu is with Siemens PTI, Minnetonka, MN 55305 USA (e-mail:
yaming.zhu@siemens.com).
K. Tomsovic is with the Min H. Kao Department of Electric Engineering
and Computer Science, The University of Tennesse, Knoxville, TN (e-mail:
tomsovic@eecs.utk.edu).
978-1-4244-8357-0/10/$26.00 ©2010 IEEE
cells can help to maintain the balance between generation and
load at the distribution level. Geographically dispersing the
resources for ancillary services should improve their
effectiveness as well as improve reliability. For example, the
small capacity of each unit benefits the system reliable
operation because the failure of any single unit has relatively
little impact on the power system. In certain configurations,
the units can provide back-up power and improve power
quality for sensitive loads.
With large numbers of DERs installed in distribution
systems, the real-time operation, control and coordination of
these units will become an issue. Two types of control
strategies have been proposed. In [4], a fully competitive retail
market not only at the transmission level but also at the
distribution level is assumed. DERs are located throughout the
power system, and are free to contract to supply load
everywhere in the system. They are allowed to enter into
contracts at the whole sale and retail levels and participate in
the power exchange, as well as to provide ancillary services to
the Regional Transmission Organization (RTO) and local
customers on a competitive basis. Based on this future
scenario, the control strategy proposed is price-based control.
All DERs are controlled in response to both primary
controllers and individual price-based signals. The difficulties
in such an approach are clear. Verifying the viability of
transactions is extremely difficult. Practically, distribution
systems are not designed to allow reverse flows and so many
transactions would not be physically realizable.
Another control strategy is proposed in [5]. The control of
DERs is based on the local information available at the power
conditioners. Through the inverters’ frequency control, the
power angle, and the flow of the real power output can be
controlled. This control can be called as local-based inverter
control. The main difficulty of this control strategy is the
coordination of their operations, especially with large amounts
of DERs installed in the distribution system.
This paper explored the feasibility and benefits for DERs to
provide ancillary services at the distribution level. It presented
the Automatic Generation Control (AGC) type control
strategy for the real time control of DERs in distribution
systems. Two control modes are considered, which are
competitive control mode and proportional control mode.
These two control modes are simulated and compared in a
distribution system. Simulation results show that the
proportional control mode is more effective than competitive
control mode for controlling DERs in distribution systems.
2
With the AGC type control strategy, the reliability of
distribution system is satisfied and the impact of DERs on
transmission system is limited.
The organization of this paper is as follows. Section II
introduces the feasibility and benefits of providing ancillary
services from DERs at the distribution level. The AGC type
control strategy with the consideration of two control modes
(competitive control mode and proportional control mode) are
presented in Section ΙΙΙ. Simulation results for load following
and contingency reserve performance from DERs are
compared between two control modes in Section IV.
Conclusions are given in Section V.
II. DERS AS PROVIDERS OF ANCILLARY SERVICES
The Federal Energy Regulatory Commission (FERC)
defines ancillary services in [9] as those “necessary to support
the transmission of electric power from seller to purchaser
given the obligations of control areas and transmitting utilities
within those control areas to maintain reliable operations of
the interconnected transmission system.”
Ancillary services have different types: regulation, load
following, contingency reserve, frequency response, reactive
power supply from generation sources, system black start
capability, etc. Different types of ancillary services are quite
different in terms of time frame, characteristic features, and
operation. Frequency response, regulation, load following,
and contingency reserve are all real power ancillary services
and mainly used to maintain the desired level of reliability in
system’s normal operation and outages. Although these
services can be acquired from a competitive ancillary service
markets, there are several reasons for local procurement,
including:
• Transmission congestion may prevent the use of
remote sources.
• Local services are generally more effective for the
reliability of specific region, especially for voltage
control.
• Providing ancillary services from several local small
resources is more reliable than a single, or a few, large
central resource(s).
DERs are potentially valuable providers of regulation, load
following, and contingency reserve for the local control area.
With the advantages of small capacity, when sited locally
within the distribution system, they may contribute
significantly to distribution system reliability. Reactive power
supply from generation sources and system black start
capability are highly location dependent. In a distribution
system, these two services could be totally provided from
DERs.
In [1], it is demonstrated that DERs such as microturbines
and fuel cells are capable of providing load following service
in the distribution system. By providing reactive power
support from DERs and optimizing the shunt capacitors’
switching, the real power losses in the distribution feeder can
be minimized [7]. With more and more DERs providing
energy and ancillary services in the distribution systems, it
becomes imprtant to develop control strategies to efficiently
coordinate DERs’ operation in distribution systems.
III. AGC TYPE CONTROL STRATEGY
Automatic Generation Control (AGC) is used for
maintaining system frequency and controlling tie-line flows to
the scheduled values [6]. With the consideration of AGC type
control strategy for the real-time operation of DERs in a
distribution system, the following assumptions are made:
• The distribution system has a strong connection with
the transmission system. Most of power is delivered
from the transmission system to the distribution feeder.
In addition, DERs provide ancillary services and small
amount of energy in the distribution system;
• The real-time operation of DERs focuses on slow
dynamics, such as providing ancillary-services. Fast
dynamics are not considered;
• Because the feeder load is small relative to overall
power system, the frequency deviation is assumed zero.
• Bilateral contracts to provide ancillary services among
DERs on a given feeder are not allowed. That is, the
ancillary services must be coordinated at the substation
or transmission level;
• There is a simple communication system in the
distribution system. The communication network is
simply modeled as a fixed time delay of 0.5 s and lost
messages or other failures are not considered. The
feeder can measure the power supply to the substation,
conceptually a “tie-line” flow, and then send related
information to all DERs. In this way, the DERs work
together to provide ancillary services;
• For ancillary services acquired from the markets, the
feeder is assumed to be able to obtain the required
quantity at the market rate from the transmission
system as necessary;
With this AGC type control, the tie-line flow between the
feeder and the connected transmission system is maintained at
the desired value. The DERs are coordinated to provide the
required ancillary services. Balance between generation and
load in the distribution system is maintained during normal
operation and outages if possible. Two modes of real-time
control are considered. The first is called competitive control
mode, where the feeder controller broadcasts the information
of tie-line mismatch and the type of required ancillary service
to all DERs. The DERs which have been dispatched compete
to supply as much of the service as possible in order to receive
payment. Notice this supply is also self-limited by DERs to be
within their dispatched quantities. The competitive control
mode allows relatively independent operation of DERs. The
second mode is called proportional control mode. The feeder
controller sends the tie-line flow mismatch individually to
each DER according to the percentage the unit has agreed to
3
supply. This means that the DERs need to supply the ancillary
service proportionally to their dispatched quantity. It is similar
with the traditional central control mode and requires the
substation to have complete information about the connected
DERs.
IV. SIMULATION RESULTS
A. Example Distribution System
The proposed AGC type control strategy for DERs is
implemented for the system in Fig. 1, which is based on a
distribution feeder in the Kumamoto area of Japan [7]. The
network parameters can be found in [8]. The distribution
system base value is 10 MVA with a line voltage of 6.6 kV.
There are six DERs integrated in the distribution system, each
consists of several Solid Oxide Fuel Cell (SOFC) stacks or
microturbines which are modeled as described in [1]. These
DERs are classified in Table I.
The total load in this distribution system is Pload =18.9
from DERs. A total load increase of 3% is simulated. Loadfollowing service is provided by the DERs installed in the
example distribution system.
It is assumed that there is no load-following service
acquired from the transmission system here, all is selfprovided from the DER units. Simulation results under the
competitive and proportional control modes for a 3% total
step load increase are shown in Fig. 2 and Fig. 3, respectively.
From the simulations, the following conclusions can be
drawn:
• Under both the competitive and proportional control
modes, DERs are capable of providing effective loadfollowing service;
• The maximum deviation and the time to return to
scheduled tie line flow is significantly better in the
proportional mode. Thus, assuming the DERs can be
dispatched fairly using the centralized proportional
approach, this method provides better performance.
MW, Qload =1.3 Mvar.
1.1
G 4
1
2
3
5
4
6
1
SS
G 5
12
13
14
Normalized Real Power
G2
15
G14
7
8
9
10
11
0.9
Load
Tie Line Flow
G2 Output
G7 Output
0.8
0.7
0.6
G11
0.5
G 7
0.4
Fig. 1. Kumamoto 15-bus distribution system diagram.
0
50
TABLE I
CLASSIFICATION OF DISTRIBUTED ENERGY RESOURCES
Type
G2
3-SOFC
900
G4
2-SOFC
600
G11
2-SOFC
600
G5
3-microturbine
750
G7
4-microturbine
1000
G14
3-microturbine
750
Rated Power
Prate
(kW)
B. Load Following Performance
Load following maintains interconnection frequency, and
keeps generation and load balance within the control area but
on scale of several minutes to hourly. In so doing, load
following resources should follow the hour-to-hour and daily
changes in customer loads.
Load variations in the example distribution system are
considered for simulating the load following performance
150
Time (s)
200
250
300
(a) load following performance
1.04
Load
Tie Line Flow
1.03
Normalized Real Power
DERs
100
1.02
1.01
1
0.99
0.98
0
50
100
150
Time (s)
200
250
(b) tie-line flow variation
Fig. 2. Load following in competitive control mode
300
4
1.1
• Given a strong and reliable inter-tie with the
transmission system, sudden large and unanticipated
disturbances can be managed effectively with the
combined supply of contingency reserve from
transmission system and local DERs. This provides an
increased security for the distribution system without
excessively taxing the distribution system.
• Similar to the load following performance, the
proportional control approach is more effective than
that of competitive control.
Normalized Real Power
1
0.9
Load
Tie Line Flow
G2 Output
G7 Output
0.8
0.7
0.6
0.5
1.1
0.4
0
50
100
150
Time (s)
1
Normalized Real Power
(a) load-following performance
1.04
Load
Tie Line Flow
Normalized Real Power
1.03
Tie Line Flow
G2 Output
G7 Output
0.9
0.8
0.7
0.6
1.02
0.5
1.01
0.4
0
10
20
30
1
50
60
70
80
70
80
(a) contingency-reserve performance
0.99
0.98
40
Time (s)
1.025
0
50
100
150
Time (s)
(b) tie-line flow variation
Fig. 3. Load following in proportional control mode
C. Contingency Reserve Performance
Contingency reserve consists of spinning reserve and
supplemental reserve. The differences between them are: one,
spinning reserve must be synchronized to the grid and be
ready to respond immediately to an outage, and two,
supplemental reserve is far cheaper than spinning reserve,
primarily because it involves very little operating cost and no
opportunity cost. Contingency reserve should be distributed
among as many units as possible in the control area for better
reliability.
For consideration of outages, the plant G5 separates from
the system. Contingency reserve service is supplied from both
the transmission system and local DER units. The
transmission system can supply contingency reserve up to 200
kW at the rate of 40 kW/s during an outage of a generator.
The needed reserve is assumed to be determined by the
substation controller. Here again, the simulations compare the
competitive and proportional control approaches, which are
given in Fig. 4 and Fig 5, respectively. From these
simulations, the followings are observed:
Normalized Tie Line Flow
1.02
1.015
1.01
1.005
1
0
10
20
30
40
Time (s)
50
60
(b) tie-line flow variation
Fig. 4. Contingency reserve in competitive control mode
5
Proportional control mode and competitive control mode are
two control modes to be considered and compared. The
competitive control mode allows relatively independent
operation of DERs. With the proportional control mode, it is
more effective to provide load following and contingency
reserve services from DERs. Both control modes with AGC
type control strategy are demonstrated to be capable for the
coordination of DERs for a moderate size distribution system.
1.1
Normalized Real Power
1
0.9
0.8
Tie Line Flow
G2 Output
G7 Output
0.7
VI. REFERENCES
0.6
[1]
0.5
[2]
0.4
0
10
20
30
40
Time (s)
50
60
70
80
[3]
(a) contingency-reserve performance
[4]
Normalized Tie Line Flow
1.015
[5]
[6]
1.01
[7]
1.005
[8]
[9]
1
0
10
20
30
40
Time (s)
50
60
70
80
(b) “tie-line” flow variation
Fig. 5. Contingency reserve in proportional control mode
V. CONCLUSIONS
Distributed Energy Resources are potentially valuable
providers of ancillary services such as load following and
contingency reserve in distribution systems. As greater
numbers of DERs are incorporated into the distribution
systems, there will come to the point where the DERs must be
dispatched and their operation carefully coordinated. The
radial structure of the distribution system and the small size of
the DERs suggest that this coordination is best performed at
the substation level. To coordinate through central markets it
may need excessive complexity for those markets with little
effective increase in market competitiveness.
AGC type control strategy proposed in this paper is to
control and coordinate the operation of DERs installed in the
distribution system, under the situations of load variations or
system outage in the distribution level. With the AGC type
control, the tie-line flow between the feeder and the connected
transmission system is maintained at the desired value. The
DERs are coordinated to provide the required ancillary
services during normal operation and outages if possible.
Y. Zhu and K. Tomsovic, “Development of models for analyzing the
load following performance of microturbines and fuel cells,” Journal of
Electric Power Systems Research, Vol. 62, Issue 1, May 2002, pp. 1-11.
H. Salehfar and A. Wehbe, “Direct control of residential water heater
loads to reduce power system distribution losses,” Proceedings of the
IEEE/PES 2001Winter Meeting, Columbus, Ohio, USA, Jan. 2001.
T. Griffin, K. Tomsovic, D. Secrest, and A. Law, “Placement of
dispersed generations systems for reduced losses,” Proceedings of the
33rd Hawaii International Conference on Systems Sciences, Maui,
Hawaii, Jan. 2000.
Judith B. Cardell, “Integrating small scale distributed generation into a
deregulated market: control strategies and price feedback,” Ph.D
Dissertation, Massachusetts Institute of Technology, Sep. 1997.
R. H. Lasseter, “Control of distributed resources,” Proceedings of the
1998 International Conference on Bulk Power Systems Dynamics and
Control ΙV – Restructuring, Santorini, Greece, Aug. 1998, pp. 323-330.
A. J. Wood and B. F. Wollenberg, Power Generation, Operation, and
Control, 2nd ed., New York: John Wiley & Sons, 1996, pp. 328-356.
Y. Zhu and K. Tomsovic, "Optimal distribution power flow for systems
with distributed energy resources," International Journal of Electric
Power and Energy Systems, Vol. 29, Issue 3, March 2007, pp. 260–267.
S. Li, K. Tomsovic, and T. Hiyama, "Load Following Functions Using
Distributed Energy Resources," Proceedings of the 2000 IEEE PES
Summer Meeting , Seattle, July 2000, pp. 1756-1761
Federal Energy Regulatory Commission, “Notice of Proposed
Rulemaking: Docket No. RM95-8-000,” Mar. 1995.
VII. BIOGRAPHIES
Y. Zhu (SM’2003) received the B.S. from Tsinghua
University, P.R. China, in 1989, the M.S. from the
Graduate School of Nanjing Automation Research
Institute, P.R. China, in 1992, and the Ph.D. degree
from Washington State University, Pullman, in 2002,
all in Electrical Engineering. He is currently with
the consulting department at Siemens PTI. He is
involved in transmission planning studies, generator
interconnection
studies,
transmission
service
request studies, and dynamic model verification. He
was with Midwest ISO from 2002 to 2008 as a senior
planning engineer, and with Nanjing Automation
Research Institute (NARI), China as an R & D project
manager responsible for development of various power
system automation products from 1992-1998.
K. Tomsovic (F’2007) received the B.S. degree in
electrical engineering from Michigan Technological
University, Houghton, in 1982 and the M.S. and Ph.D.
degrees
in
electrical
engineering
from
the
University of Washington, Seattle, in 1984 and 1987,
respectively.
Currently,
he
is
Head
and
CTI
Professor
of
the
Department
of
Electrical
Engineering and Computer Science at University of
Tennessee, Knoxville. Visiting University positions
have
included
Boston
University,
Boston,
MA;
National Cheng Kung University, Tainan, R.O.C.;
National Sun Yat-Sen University, Kaohsiung, Taiwan,
R.O.C.; and the Royal Institute of Technology,
Stockholm, Sweden. He was on the faculty of
Washington State University from 1992-2008. He held
the Advanced Technology for Electrical Energy Chair
at Kumamoto University, Kumamoto, Japan, from 1999
6
to 2000 and was an NSF program director in the ECS
division from 2004 to 2006.