Power System Operation with Large Scale Stochastic Wind Power Integration: Interval Arithmetic Based Analysis and Optimization Methods

229 Pages·2017·7.94 MB·English

by  Tao Ding (auth.)

Springer Theses
Recognizing Outstanding Ph.D. Research
Tao Ding

Power System
Operation with
Large Scale
Stochastic Wind
Power Integration
Interval Arithmetic Based Analysis and
Optimization Methods
Springer Theses
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Tao Ding
Power System Operation
with Large Scale Stochastic
Wind Power Integration
Interval Arithmetic Based Analysis
and Optimization Methods
Doctoral Thesis accepted by
Tsinghua University, Beijing, China
123
Author Supervisor
Dr. TaoDing Prof. HongbinSun
Xi’anJiaotong University TsinghuaUniversity
Xi’an Beijing
China China
ISSN 2190-5053 ISSN 2190-5061 (electronic)
SpringerTheses
ISBN978-981-10-2560-0 ISBN978-981-10-2561-7 (eBook)
DOI 10.1007/978-981-10-2561-7
LibraryofCongressControlNumber:2016949622
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’
Supervisor s Foreword
Overthepastdecades,overdevelopmentofconventionalfossilenergyresultedina
range of problems, such as environmental pollution, which pose threats on human
healthandsustainability.Inrecentyears,hydro,wind,solarpower,naturalgas,and
othercleanenergyalternatives,whichareexpectedtobedominantformsofenergy
in the future, are being developed at rapid speeds to accommodate future energy
demands.
Wind power, as an alternative to fossil fuels, is one of the most important and
prominent renewable resources that is under development in an unprecedented
rapidpacearoundtheworld,duetotheincreasingelectricitydemandsandtheneed
for more environmentally benign electric power generation. Wind farm develop-
mentinChina isinfast lane too.At theendof2012,thetotal installedcapacityin
China, excluding Taiwan, was 75.32 GW, which topped USA to become the
country with most installed wind power [1, 2]. In China, however, wind resources
aremainlydistributedinnorthernandnorthwesternareasofthecountry,whichare
far from the major load centers in the eastern and coastal areas. Therefore, wind
power is centrally collected and integrated into the power grid through
long-distance transmission systems to transport the wind power to these load
centers. Take Zhangbei wind farm base in North China; for example, there are
nearly20windfarmsintegratedintothegridviaasingle220-kVtransmissionline,
while in the area there is neither conventional power plant nor load demand. In
addition, several 10-GW-level wind power bases will be built in wind-rich areas,
including Inner Mongolia, Gansu, Xinjiang, Hebei, and Jiangsu, by the end of
2020.Theselarge windfarm bases areexpectedtobe connectedtothepowergrid
via centralized integration.
However, large-scale wind power integrated into power system brings about a
great challenge to traditional power flow analysis and economic dispatch decision.
Unlike traditional thermal generators, the generation output of wind power is
always uncertainandvarieswithnaturalconditionsincludinglocation,windspeed
anddirection,airtemperature,andhumidity.Thestrongrandomnessofwindpower
makes it difficult to predict and control. Moreover, as mentioned above, when
v
vi Supervisor’sForeword
compared to other countries, wind power consumptive problem in China is more
prominent since the wind power resource distributes unevenly, mostly in areas far
away from the load and difficult to achieve dispersive elimination locally; thirdly,
thewindfarmgrowthrateismuchhigherthanthatofthelocalpowerconsumption.
Due to the transmission capacity limitation of transmission corridors, safety and
stability may be compromised, resulting in serious wind curtailment.
Therefore,itisurgenttodevelopnewtechniquestoaccommodatewindpowerin
asecureandeconomicway.ThisPh.D.dissertationmainlyfocusesonthesetopics
to address uncertainties. Based on interval mathematics, the wind power uncer-
tainties are modeled as interval numbers, which facilitates the modeling of wind
power. Furthermore, this book studies the mathematical modeling and methods to
interval power flow, interval economic dispatch, and interval robust economic
dispatch. Its breath is impressive and seldom seen in the context of a Ph.D.
dissertation.
Beijng, China Prof. Hongbin Sun
July 2016
Preface
Large-scale wind power integrated into power system brings about a great chal-
lengetotraditionalpowerflowanalysisandeconomicdispatchdecision.Thisbook
mainly focuses on these topics to address uncertainties. Based on interval mathe-
matics, the wind power uncertainties are modeled as interval numbers, which
facilitates the modeling of wind power. Furthermore, this book studies the math-
ematicalmodelingandmethodstointervalpowerflow,intervaleconomicdispatch,
and interval robust economic dispatch.
In Chap. 1, literature review of related works is presented, and their contribu-
tions to the book are summarized.
In Chap. 2, as the basis of this book, mathematical theories of interval calcu-
lationandoptimalplanningareintroduced,includingdefinitionofintervalnumber,
the method for the linear equations with right-hand interval, interval optimal
solution, and self-adaptive two-stage robust interval optimization.
Chapter 3 investigates the interval power flow with uncertain wind power,
includingDCintervalflow,ACintervalflow,anddistributionsystemintervalflow,
in which a preprocessing iteration and parallel calculation are adopted to prevent
overconservativeness;theDCpowerflowistakenasanexampletodiscusspower
flow calculation with constraints and dynamic interval power flow model.
In Chap. 4, the traditional economic dispatch is expanded to interval economic
dispatch in which interval of wind power output is considered; in fact, interval
optimization can be seen as the sensitive analysis of the traditional economic dis-
patch,becauseitprovidesareferenceforsystemdispatchersabouttheinfluenceof
windpoweruncertaintyontheresultofeconomicdispatch;intervaloptimizationis
also different from sensitive analysis because interval optimization can consider
parametersthatchangeoverawideintervalwhilesensitiveanalysisusuallyfocuses
ontheparameterschangingwithinatightrange;itisworthnoticingthattheremight
be no feasible solution under the wind power uncertainty, so a minimal wind
curtailment and soft transmission constraints are adopted to guarantee feasibility.
InChap.5,therobustoptimizationstrategyisadoptedtosearchfor theoptimal
solution.TheresultfromChap.3isusuallymoresuitableforevaluationratherthan
dispatching order. Dispatching order should be a concrete number instead of an
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viii Preface
intervalnumber,whilerobustoptimizationcanprovideaconcretedispatchingorder
thatsatisfysecurityconstraintsinuncertainscenarios.Twotypesofintervalrobust
optimization models are discussed in this chapter: One is the self-adaptive interval
robust optimization that can guarantee power balance by the introduction of AGC
participation factor. Itisshownthat thisparticipation factorhassome effect onthe
conservativeness of the robust optimization. If the participation factor can be reg-
ulated real time in real-time energy market (within 5 min), then the conservative-
ness of the robust optimization can be reduced; the second type is to perform
economic dispatch under wind power uncertainty considering topology reconfig-
uration, whichisalong-term problemincomparisonwiththefirsttype,whichisa
real-time problem. From the perspective of mathematical modeling, two-stage
robusteconomicdispatchisatri-leveloptimizationmodel,whichcanbeturnedinto
a mixed-integer optimization problem by Benders decomposition, and the optimal
result can be achieved by column constraint generation that introduces cutting
planes; while the self-adaptive interval robust optimization model is a bi-level
problem, which can be turned to a convex second-order model by adding dummy
variables; the most significant problem in the robust optimization is to reduce the
conservativeness,andinthisbook,theconceptofrobustcostisintroducedtoreach
the balance between security and economy. Finally, some practical problems in
power system modeling are discussed, and their mathematical models and algo-
rithms are provided.
InChap.6,improvedonlinelarge-scaleeconomicdispatchproblemsarestudied.
Itisnothardtounderstandthatrealpowersystemhasaquitelargescale;therefore,
the dispatching problem under multiple time periods can be very complex. Such
optimization problem is mostly expected to be fast ;and efficiently solved for
real-timemarketregulationandforintradaydispatchinginarollinghorizon.Todo
so,twoperspectives areprovidedto improve onlineeconomicdispatching:Firstis
to reduce redundant security constraints through offline simulation to simplify the
model, and second is to use parallel optimization approaches to increase compu-
tation speed.
Chapter 7 summarizes the works and proposes future research direction.
The draft of this book is the Ph.D. dissertation of Tsinghua University. Due to
ourlimitedknowledge,thisbookmightcontainmistakesandtypos.Pleasefeelfree
to e-mail us whenever you find any problems within this book. We are more than
happy to revise this book on your notice.
Xi’an, China Tao Ding
Parts of this thesis have been published in the following documents:
Journals
[1] TaoDing,RuiBo,WeiGu,HongbinSun,“Big-MbasedMIQPmethodfor
economic dispatch with disjoint prohibited zones,” IEEE Transactions on
Power Systems, vol. 29, no. 2, pp. 976–977, March 2014.
[2] TaoDing,RuiBo,WeiGu,HongbinSun,“Absolutevalueconstraintbased
method for interval optimization to SCED model,” IEEE Transactions on
Power Systems, vol. 29, no. 2, pp. 980–981, March 2014.
[3] Tao Ding, Rui Bo, Fangxing Li, Hongbin Sun, et al, “Interval power flow
analysis using linear relaxation and optimality-based bounds tightening
(OBBT) methods,” IEEE Transactions on Power Systems, vol. 30, no. 1,
pp. 177–188, 2015.
[4] Tao Ding, Qinglai Guo, Rui Bo, Hongbin Sun, and Boming Zhang,
“AStatic Voltage Security Region for Centralized Wind Power Integration
−PartI:ConceptandMethod,”Energies,vol.7,no.1,pp.420–443,2014.
[5] Tao Ding, Qinglai Guo, Rui Bo, Hongbin Sun, and Boming Zhang,
“AStatic Voltage Security Region for Centralized Wind Power Integration
− Part II: Applications,” Energies, vol. 7, no. 1, pp. 444–461, 2014.
[6] TaoDing,RuiBo,FangxingLi,HongbinSun,“OptimalPowerFlowwith
the Consideration of Flexible Transmission Line Impedance”, IEEE
Transactions on Power Systems, vol. 31, no. 2, pp. 1655–1656, 2015.
[7] Tao Ding, Rui Bo, Qinglai Guo, Hongbin Sun, “A Robust Two-level
Coordinated Static Voltage Condition for Centralized Wind Power
Integration”,IEEETransactions onSmart Grid, vol.7,no. 1,pp. 460–470,
2015.
[8] Tao Ding, Rui Bo, Fangxing Li, Hongbin Sun, “A Bi-level Branch and
Bound Method For Economic Dispatch with Disjoint Prohibited Zones
Considering Network Losses”, IEEE Transactions on Power Systems, vol.
30, no. 6, pp. 2841–2855, 2015.
[9] Tao Ding, Rui Bo, Fangxing Li, Hongbin Sun, “Exact Penalty Function
BasedConstraintRelaxationMethodForOptimalPowerFlowConsidering
Wind Generation Uncertainty,” IEEE Transactions on Power Systems, vol.
30, no. 3, pp. 1546–1547, 2015.
[10] Tao Ding, Linquan Bai, Zhaohong Bie, Fangxing Li, “An Adjustable
Robust Optimal Power Flow with the Price of Robustness for Large-scale
PowerSystems,”IETGeneration,Transmission&Distribution,vol.10,no.
1, pp. 164–174, 2016.
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