A Consideration of the Wind Power Benefits in Day-Ahead Scheduling of Wind-Coal Intensive Power Systems

236 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 28, NO. 1, FEBRUARY 2013

A Consideration of the Wind Power Benefitsin Day-Ahead Scheduling of Wind-Coal

Intensive Power SystemsCaixia Wang, Student Member, IEEE, Zongxiang Lu, Member, IEEE, and Ying Qiao

Abstract—This paper studies day-ahead unit commitment inwind-coal intensive power systems. Due to their long start up time,high start up cost, and high minimum stable output, coal-firedgenerators do not provide a favorable environment for accommo-dating variable wind generation. The reduced efficiencies resultingfrom the coal-fired generation side as measured in increased fuelconsumption and emissions can greatly undermine the windpower benefits to the system if wind generation and coal-firedgeneration are not properly coordinated. Special attention in thestudy is given to the wind power benefits to the system in fuel sav-ings and in reduction of emissions. Based on the wind powerforecast, the stochastic nature of wind power is treated in twoparts, i.e., wind power variability and wind power uncertainty.Unit commitment is studied using wind power variability anduncertainty separately in different wind power dispatch modesand using respectively different spinning reserve procurementstrategies. System performance indices are then applied to deter-mine the optimal wind power dispatch mode and optimal spinningreserve procurement strategy to capture optimal wind powerbenefits for the system. A simulation system characterized bytypical wind-coal features is constructed to model and to conductthe studies. The results show that taking wind power curtailmentas a control option and using wind as a reserve provider improvethe wind power benefits to the system.

Index Terms—Dispatch mode, spinning reserve, unit commit-ment, wind power.

I. INTRODUCTION

A N increasing number of wind farms worldwide are beingbuilt each year. In China, the total installed wind capacity

reached 44.73 GW at the end of 2010 [1]. It is expected to reach200 GW by 2020 [2]. Integrating such a large amount of windpower into bulk power systems is a great challenge, especially inwind-coal intensive power systems which lack flexible genera-tors to coordinate with variable wind generation. In China, coal-fired generators make up over 80% of the total generation inmost wind-integrated power systems. The combined operation

Manuscript received August 31, 2011; revised September 24, 2011, January03, 2012, and April 23, 2012; accepted June 05, 2012. Date of publication July23, 2012; date of current version January 17, 2013. This work was supported inpart by the National Natural Science Foundation of China (No.51077078) andin part by the National Science and Technology Infrastructure Program of China(No.2011BAA07B). Paper no. TPWRS-00824-2011.The authors are with the State Key Lab of Power Systems, Department

of Electrical Engineering, Tsinghua University, Beijing 100084, China(e-mail: [email protected]; [email protected];[email protected]).Color versions of one or more of the figures in this paper are available online

at http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/TPWRS.2012.2205280

of wind generation and coal-fired generation is a key problem inthe operation domain. This paper studies day-ahead unit com-mitment (DAUC, abbr. UC) in wind-coal intensive power sys-tems. UC is a fundamental procedure in daily power systemoperation that relates to the coordination of wind power andcoal-fired generation.UC involving wind power has been a rich area for research.

In [3]–[7], stochastic unit commitment models in which the re-serve dispatch decisions are naturally optimized in a stochasticprogramming formulation are constructed. In [8], a determin-istic UC model is constructed in which a certain percentage offorecasted wind is taken to be the extra reserve. In [9], a hybridprobabilistic/deterministic UC model is formulated, which ex-plicitly models the day-ahead predicted residual demand proba-bility density function. In [10], emission constraints are added tothe UC formulation. In [11] and [12] the impact of wind poweron such system performance indices as cost and emissionreduction are studied with respect to the Irish power system.The previous research has made a significant contribution to

the formulation of UC with wind power and yielded invaluableinsights into the impact of wind on power system operation.One problem with most of these studies, though, is that theytreat wind power generally as “negative” load and model thestochastic nature of wind to guarantee system security. The dualeffect of wind power on system fuel savings and emissionsis not given full discussion in the UC modeling process. Theresults given, therefore, do not properly capture the wind powerbenefits to the power systems.Generally, wind power is “green power”. However, the vari-

ability in wind power can create reduced efficiency and evenfrequent re-start-ups of conventional generators as shown in[13] and [14]. This leads to increased fuel consumption and

emissions. Coal-fired generators take a long time to startup, induce high start up costs and have a high minimum stableoutput level. The negative effects of wind power on coal-firedgenerators can greatly undermine the wind power benefits tothe system if wind generation and coal-fired generation are notproperly coordinated. Therefore, in wind-coal intensive powersystems, a more detailed model of UC needs to be carried out toconsider the dual effect of wind power to provide more insightinto the dispatch of wind power. Some initial work has beendone by other researchers. References [8] and [9] give simula-tion results to show that wind power curtailment leads to bettersystem operation cost. References [11] and [12] study the im-pacts of wind on system cost and emission in the Irishsystem, which relies mainly on gas turbines. The conclusions

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WANG et al.: CONSIDERATION OF THE WIND POWER BENEFITS IN DAY-AHEAD SCHEDULING 237

presented in the above research, however, may not be applicableto the wind-coal intensive power systems used in China.This paper uses system performance indices related to wind

power benefits as metrics to coordinate wind generation andcoal-fired generation in the DAUC. The wind power benefits inthis paper refer to the net benefits wind power brings to powersystems, as measured in fuel savings and emissions reduction.Based on the wind power forecast, the stochastic nature of windpower in this paper is decomposed into two parts, i.e., windpower variability and wind power uncertainty. The forecastedwind power is taken as wind power variability and dispatchedtogether with coal-fired generation. The wind power forecasterror is taken as wind power uncertainty and is expected to beabsorbed by spinning reserve. Considering wind power vari-ability, UC is studied in five day-ahead dispatch modes. Thedispatch modes differ in terms of their wind dispatch prioritiesas indicated by different wind curtailment options and UC ob-jective functions. Considering wind power uncertainty, UC isstudied in terms of four spinning reserve procurement strate-gies. They differ in terms of how the upward/downward spin-ning reserve is procured. The possibility of using wind powerto provide spinning reserve is also modeled. A small wind-coalintensive power system that mimics the characteristics of thepower systems in China’s wind-rich areas is constructed for thesimulation study. It is based on the IEEE RTS-96 system [15].Wind data fromwind farms in the Eastern Interconnection in theUS [16] is used. The different wind power dispatch modes anddifferent spinning reserve procurement strategies are analyzedwith the simulation system.The remainder of this paper is organized as follows. In

Section II, decomposition of wind power and the UC problemare described. In Section III, five day-ahead dispatch modesconcerning wind power variability and four cases of spinningreserve procurement concerning wind power uncertainty areprovided, and the performance indices used in the UC formu-lation discussion are presented. In Section IV, a simulationsystem is constructed and simulation studies are conducted.Section V summarizes the study’s conclusions.

II. DECOMPOSITION OF WIND POWER AND THE UC PROBLEM

An appropriate modeling of wind power is important tofully capture its impact on fuel saving and emission reductionwhen coordinating it with conventional generation. Generally,wind power forecasting tools provide wind power forecastvalues in 15-min intervals. If wind power is forecasted with100% accuracy, we can deal with the wind power similarly toconventional generation in UC. The only difference to noteis the variable nature of wind power output. Otherwise, anincreased amount of spinning reserve should also be procuredto account for the wind power forecast error. Accordingly, tobetter understand the different features of wind power impacton UC, the wind power output in this paper is divided intotwo major parts, i.e., variability and uncertainty, as shown inFig. 1. Here, the variability part denotes the forecasted value ofwind power, changing like daily load valley-peak variation. Itcan be balanced with start-ups and the generation scheduling

Fig. 1. Wind power variability and wind power uncertainty.

Fig. 2. Dispatch modes of DAUC with wind power.

of coal-fired generators. The uncertainty part denotes the dif-ference between real wind power output (the average of realtime wind power variation during the forecast interval) and theforecasted wind power, i.e., wind power forecast error, whichcan be absorbed by the spinning reserve.Based on the decomposition of wind power, the UC mod-

eling in wind-coal intensive power systems can be decomposedinto two problems: one is the optimal dispatch of wind powerand coal-fired generation that focuses on the coordination of thevariable wind output and coal-fired generators; the other is theoptimal spinning reserve procurement strategy, which studiesthe spinning reserve arrangement for wind power in DAUC. Thetwo UC problems are studied separately in the following paper.

III. MANAGING WIND POWER VARIABILITY ANDUNCERTAINTY IN DAY-AHEAD UNIT COMMITMENT

A. Managing Wind Power Variability: Day-Ahead DispatchModes

1) Day-Ahead Dispatch Modes: This section examines windpower dispatch in day-ahead scheduling with an emphasis onthe problems created by wind power variability to the overallpower system. Five dispatch modes, as shown in Fig. 2, are con-sidered as alternatives in coordinating wind power and coal-fired generation. They are different in the following two ele-ments.

Dispatch Priority Given to Wind Power: Due to the posi-tive role of wind power in emission reduction and fuel saving,policy incentives are used in many countries to promote windin power systems as a priority [17], [18]. This paper considers


three scenarios for wind dispatch priority ranked from high tolow:1) Guaranteed wind power dispatch: Wind power is fullydispatched as long as the security of power system op-erations is not threatened. Current wind power dispatchin China follows this practice [17].

2) Privileged wind power dispatch: Wind power is givenpriority dispatch, but wind curtailment can be used as acontrol option of wind generation in DAUC whenevernecessary.

3) General wind power dispatch: Wind power and coal-fired generators participate equally in DAUC and com-pete according to their generation costs for dispatch.This may become more promising in the future whenwind power can be utilized cheaply enough.

UCObjective Function: The UC objective functions of thefive dispatch modes are one of the following:1) Generation cost of coal-fired generators2) Generation cost of coal-fired generators + emissionpenalty cost

3) Generation cost of coal-fired generators + emissionpenalty cost + Generation cost of wind power

The generation cost of coal-fired generators in this paperrefers to the fuel cost induced by generator start up and onlineoperation, instead of the cost calculated based on bidding pricesin the market. The emission penalty cost in the objective func-tion is used as a type of emission constraint which incorporatesenvironmental considerations into UC optimization.The overall social benefits as presented by the total genera-

tion cost and emission cost are used in this paper for commit-ting coal-fired generators and dispatching wind. Generation andemission costs of coal-fired generators are calculated with theirheat rate, fuel prices and unit emission price. Wind gener-ation cost here is composed of operation and maintenance costand capital cost (including planning and site work). Marginalcost is not used for DAUC market bid in the paper.The objective functions are partially designed to help model

the different wind power dispatch priorities in UC. The different“(dispatch method) (objective function)” combinations, asdenoted by different dispatch modes, are used purposefully tostudy the impact of different wind dispatch priorities on systemperformances. For example, general dispatch of wind power isachieved by being combined with objective three (i.e., Mode Vin Fig. 2), while priority dispatch of wind power is achieved bybeing combined with objective one or two (i.e., Modes I-IV inFig. 2).2) DAUCModel: Models of different dispatching modes are

formulated in (1)–(3). The main differences from the traditionalUCmodel are the objective functions and the introduction of thewind curtailment variable. The different wind dispatch prioritiesare indicated by different wind power curtailment penalty costs.

Mode I-II:

(1)

in which

(1a)

(1b)

(1c)

where

sum of start up and shut down cost ofconventional unit in period ($/h);

and startup cost and shut down cost ofconventional unit in period , respectively($/h);

, and binary variables. is 1 if conventional unitstarts at beginning of period , 0 otherwise.is 1 if conventional unit shuts at

beginning of period , 0 otherwise. is 1 ifconventional unit is dispatched during ,0 otherwise;generation cost of conventional unit inperiod .

is the fuel rate of conventional unit , given as fol-lows:

output of conventional unit in period t(MW);.fuel price ($/MBTU).

is penalty cost of wind power curtailment ($), which isinduced by wind power curtailment during a certain period. isunit penalty cost of wind power curtailment ($/MWh). Differentsettings are used as indicators for different wind power dis-

patch priorities. For Mode I, is a very large number so as todiscourage wind power curtailment and thus ensure guaranteedwind power dispatch. For Mode II, is 0, so that wind poweris curtailed whenever necessary without having to worry aboutthe penalty.

is wind power curtailment during (MW); isdispatch interval, e.g., 15 min; is horizon of day-ahead sched-uling, which is 24 h in this paper; is the number of conven-tional units.

Mode III-IV:

(2)

in which

emission cost of conventional unit inperiod ($/h);

emission coefficient of conventional unit;

emission price ($/ton). Theemission of wind turbines is assumed to bezero. The settings of in Mode III and IV arethe same as that in Mode I and II, respectively.

Mode V:

(3)


in which

is the cost of wind generation in period ($/h). is theunit cost of wind generation ($/MWh). is dispatched windpower in period . As wind power participates equally in DAUCwith conventional units in Mode V, system operators can usewind curtailment whenever necessary. is zero in this mode.The constraints of the UC model for the dispatch mode study

in this paper are similar to those in the traditional DAUC model[19]. The wind forecast error and load forecast error are ignoredin the dispatch mode study to highlight the variability of windand load. The following section addresses reserve constraintsconsidering wind power uncertainty. The constraints coveredhere are power balance, maximum/minimum stable operationlevels, minimum up/down times, startup time, etc.

B. Managing Wind Power Uncertainty: Spinning ReserveProcurement

1) Spinning Reserve Strategies Considering Wind Power:The wind power forecast error is taken as wind power uncer-tainty and is expected to be absorbed by spinning reserve. Thissection considers the following aspects of wind power on thespinning reserve.

Impact of Wind Power on Upward/Downward Reserve:When wind power is integrated, adequate upward spin-ning reserve should be ensured to account for the possibleunder-generation of wind power. While more downward re-serve is expected to result in the higher wind energy use rateand therefore more fuel savings and emission reduction, it mayalso increase fuel consumption and emissions on the coal-firedgenerators’ side when they are reconfigured to provide theadditional downward reserve needed. When arranging thedownward reserve, the wind power benefits need to be consid-ered.

Wind Power as a Spinning Reserve Provider: Tradition-ally, wind power is treated as “negative” load, and is seldomused to serve as the spinning reserve because of its low relia-bility. However, in wind-coal intensive power systems, there isalways a trade-off between wind power and coal-fired gener-ation control. In privileged wind power dispatch, wind powermay be curtailed in some periods so as to improve system per-formance. If the use of the otherwise curtailed wind power inproviding spinning reserve saves fuel consumption and reducesemissions of coal-fired generators, wind power should be con-sidered as a spinning reserve provider.Four spinning reserve strategies with different upward/down-

ward spinning reserve arrangements are shown in Fig. 3. DAUCwith and without wind power forecast are both considered.DAUC without wind power forecast (Case A in Fig. 3) is usedas a reference case, which is in line with the current practicein China. In Cases B-D, wind power participates in the DAUCwith wind power forecast. Besides, the extra spinning reservein Fig. 3 is used to account for wind power forecast error. Theamount of spinning reserve for load forecast error and generatoroutage are assumed to be unchanged from that of traditionalUC, e.g., 5% of peak load.

Fig. 3. Spinning reserve consideration in day-ahead scheduling.

2) Reserve Constraint Modeling:Application of Wind Power Forecast Interval: Empirical

distribution function is used to depict the probability distribu-tion of wind power forecast error. It assumes that future windpower forecast error follows the same distribution as in history[20]. In Cases C-D, which considers extra spinning reserve forwind power, 100% probability interval, as expressed in (4), isused in constructing the reserve constraints. It is obtained withthe largest negative and positive historical wind power forecasterror [21], with the elimination of extreme forecast errors, e.g.,values beyond 6 times of the forecast error standard deviation:

(4)

in which , , respectively, are the lower and upperbounds of the forecast interval.1) Reserve amount constraint

(5)

(6)

where is the output of conventional unitwhen providing upward (downward) reserve in period(MW). is the curtailed wind power inperiod when upward (downward) spinning reserve isneeded in the system (MW). and are, respec-tively, the upward and downward spinning reserve re-quirements.Assume is the upward (downward) spin-ning reserve requirement before wind power integration,we have , for all the fourcases. Assume that the 100% wind power forecast in-

terval is , then in (5)–(6)

for Case A, , for Case

B, , for Case C, and

, for Case D.2) Reserve ramp rate constraint

(7)

(8)

where , are, respectively, the ramp up rate andramp down rate of conventional unit (MW/min).


is the dispatched output of conventional unit in period(MW).

Equations (7) and (8) ensure that conventional generator iscapable of ramping between its dispatched output leveland its extreme output levels during one dis-patch interval. The ramp rate constraints for between adja-cent time intervals are the same as the traditional UC model,as shown in Appendix B. Extreme ramp rate constraints be-tween adjacent time intervals such as ramp betweenand , or, and are not considered.

Consideration of the Spinning Reserve Provision by WindPower: The provision of the downward reserve from windpower is possible through wind curtailment. The provision ofthe upward reserve using wind is possible when the amount ofdispatched wind is smaller than the lower bound of the windpower forecast interval . In this situation, the differencebetween the dispatched wind power and the lower bound of theforecast interval, which would otherwise be curtailed, can beused as upward reserve in UC. To model the possibility of windpower to provide the spinning reserve, the objective functionof the DAUC is expanded to be

(9)

in which , , are weights of , , , and

where and are the generation cost and emis-sion cost of conventional unit in period when it provides thedownward reserve; and are generation cost and

emission cost of conventional unit in period when itprovides upward reserve.Other constraints for the DAUC considering wind power un-

certainty are the same as those used in Section III-A.

C. System Performance Indices

The following system performance indices related to windpower benefits are used to compare different dispatch modesand spinning reserve strategies in the model.1) Unit Generation Cost of the System ($/MWh)

(10)

where is the total generation cost of the system ($), andgiven as

. is the total electricity demand of the systemduring the simulation period (MWh), and given as

.

2) Total Generation Cost of Conventional Units ($)

(11)

3) Unit Generation Cost of Conventional Units ($/MWh)

(12)

where is the total electricity generated by conventionalunits during the simulation period (MWh) and is given by

4) Unit Emission of the System (ton/MWh)

(13)

where is the system emission (ton); is the totalelectricity supplied during the simulation period (MWh)and is given by

5) Wind Energy Use Rate (%)

(14)

where is the total available wind energyduring the simulation period (MWh) and given by

. is the total curtailed windenergy during the simulation period (MWh) and given by

.

IV. CASE STUDY

A. Simulation System

A simulation system with the characteristics of one ofChina’s typical wind-coal intensive power systems is con-structed to evaluate the effectiveness of the dispatch modes andspinning reserve strategies presented above. The simulationsystem is constructed using generator data from the IEEE-RTS96 system and wind data from the Eastern Interconnection inthe US due to a lack of conventional unit data and wind forecastdata from China.1) Characteristics of Conventional Generators and Load:

Nine thermal units from the IEEE RTS 96 system were selectedfor use in the case study [15]. In order to mimic the variety ofthermal generators in real system, unit heat rates (correspondingto different unit sizes) are chosen to be as different as possible.Unit sizes are also chosen to be as large as possible, though theyall still seem small in size relative to standard installations. Theirparameters are given in Appendix A. Unit No.1 and Nos.5–9 arecoal-fired generators. Units Nos. 2–4 were originally oil fueledunits but treated as coal-fired generators by using the fuel priceof coal-fired generators. In addition, the minimum stable opera-tion levels of all the units were changed from 20%–30% of theirrated capacity to be 50% of the rated capacity, which is typical


TABLE ISYSTEM INDICES OF MODE I-V AT WIND PENETRATION LEVEL 25.4%

of China’s coal-fired generators. The typical p.u. load curve inreal power systems is used as the daily load curve.2) Wind Characteristics: Several wind farms were selected

from the Eastern Interconnection in the US as data sources forthe case study. The seasonal wind power variation of these windfarms is quite similar to that of wind farms in the north China.The wind power penetration level in this paper is defined as

(15)

where is the installed wind capacity, is the systempeak load. The wind power penetration level in the Inner Mon-golia Power Grid in north China, where the largest wind powerbase is located, has surpassed 25%. Therefore, 25% is taken as arepresentative wind power penetration level for the case study.3) Price Assumptions and UC Solver: The price

is assumed to be $30/ton [22], [23], and the cost of coal isassumed to be $2.25/MBTU [24]. For the simulation system,as the segmented heat rate of coal-fired generators varies be-tween 8.3–12.4 MBTU/MWh, the cost of coal-fired generationvaries between $18.7–$27.9/MWh under the coal price of$2.25/MBTU. The generation cost of wind power is set tobe $80/MWh. The DAUC model is solved using the CPLEXmixed integer programming solver in Tomlab [25].

B. Simulation Results 1: Dispatch Modes With Wind Power

1) Comparison of Different Dispatch Modes in DAUC: Thesystem performance indices for Modes I-V with wind powerpenetration levels being 25.4% are shown in Table I.Comparison of the system indices in Mode I (guaranteed

wind power dispatch) and Mode II (privileged wind powerdispatch) shows that, though the wind energy use rateis smaller in Mode II, in which wind curtailment is executedwhenever necessary, the system performance indices suchas the total cost of the conventional units , the unitgeneration cost of conventional units , and the unitemissions , outperformed those in Mode I. This indicatesthat in wind-coal intensive power systems, wind curtailmentshould be used as a control option to improve wind benefitsrather than only when system security is threatened. This maybe a different feature of wind-coal intensive power systemsfrom power systems where the existence of many gas turbineswith fast startup capability and low startup costs makes windpower benefits much less impacted by accommodating windvariability. Figs. 4 and 5 show the online conventional gener-ator capacity, net load, and wind curtailment in one day withdifferent wind power dispatch priorities.As we see, the startup times for coal-fired units are less,

leading to better system economies and emissions reduc-tion in Fig. 5, even with wind curtailment.

Fig. 4. Generation schedules in a simulation day (guaranteed wind power dis-patch).

Fig. 5. Generation schedules in a simulation day (privileged wind power dis-patch).

TABLE IISYSTEM INDICES OF MODE V AT WIND PENETRATION LEVEL 25.4%

In comparing the system indices in Mode I and Mode III,as well as in Mode II and Mode IV, we see that including the

emissions cost in the objective function of the UC leadsto further reductions in emissions with a slight increase inthe generation cost of conventional generators.The results of Mode V show that wind power does not get

used at all when no priority dispatch is given to it. This is be-cause, with the emission price being 30$/ton, the wind gen-eration cost is much higher than the sum of the generation costand the emission cost of conventional units. Thus, in thisoption wind power loses its competitive edge in DAUC.2) Impact of the Wind Generation Cost and Price On

System Operation: In Mode V, the cheaper the wind genera-tion cost and the higher the price, the more competitivewind power becomes. Tables II and III show the variation insystem performance indices with the wind generation cost and

price respectively. As we see, with the decreasing windgeneration cost and increasing price, the wind energy userate increases while emissions decline. This shows the in-creasing competitive advantages of wind power in the DAUC.


TABLE IIISYSTEM INDICES OF MODE V AT WIND PENETRATION LEVEL 25.4%

C. Simulation Results 2: Impact of Wind Power on SpinningReserve

1) Comparison of Different Spinning Reserve ProcurementStrategies: At a wind power penetration level of 25.4%, thesystem performance indices of each spinning reserve procure-ment case are shown in Table IV. In all the cases, guaranteedwind dispatch is used.By comparing Cases B-D cost indices, in which the wind

power participates in DAUC with wind power forecast, withCase A, we can see that and increase significantly. Theincrease in and in Cases B-D can be attributed to two fac-tors. One is the reduced efficiency of the coal-fired units in ac-commodating the variability of wind power when giving windpower guaranteed dispatch. The other is the extra spinning re-serve procurement to meet the wind power forecast error. Theincrement of and in Case B compared to Case A reflectsthe impact of the first factor, whereas the increment of andin Cases C-D compared to Case B reflects the impact of the

second factor. We can see that the cost increment caused by thefirst factor is much bigger than that caused by the second factor.In Case D, the extra downward spinning reserve is procured

for wind compared with Case C in order to absorb more windwhen the wind power generated exceeds the forecasted. But re-sults in Table IV show that by doing so, and increase,while stays almost the same. This is because the ability ofthe coal-fired units is so limited that no more wind power canbe accommodated. The imposition of increased reserve require-ment under this condition increases and while does notimprove. The increased reserve requirement is satisfied by cur-tailing wind power with a high penalty cost.The last column in Table IV show the interrupted load in each

case. As we see, there is a small amount of interrupted load inCase B. When extra upward reserve is procured, as in CasesC and D, load interruption is avoided. This indicates that theupward reserve increment is necessary when wind participatesin the DAUC.2) Impact of Wind Power Dispatch Priorities on System

Performances When Procuring the Spinning Reserve: Table Vshows the system performance indices for Case B with differentwind dispatch priorities. The system performance indices forCase A are provided as a reference case in the table.As can be seen, Case B* outperforms both Case B and A

in and . Therefore, when procuring the spinning reserve,taking wind curtailment as a control option leads to bettersystem economies and emissions as well. This is anotherconfirmation of the conclusion made in Section IV-B.3) Impact of Considering the Spinning Reserve Provision by

Wind Power on System Performances: When wind power par-ticipates in the DAUC and wind power is given privileged dis-

TABLE IVCOST INDICES WITH DIFFERENT CASES

TABLE VIMPACT OF WIND POWER UTILIZATION PRINCIPLE ON SPINNING RESERVE

Fig. 6. Downward spinning reserve allocation in DAUC.

patch—i.e., wind power curtailment can be taken as a controloption to improve wind power benefits—there is the possibilitythat wind can be used as the spinning reserve provider in theDAUC. Case C is used as an example for this discussion. Here,the downward reserve provided by wind means curtailed windin real time system operation when the real load is smaller thanthe forecasted load. The upward reserve provided by wind heremeans the power supplied by wind in real time when the realload is greater than forecasted.

Possibilities for Wind Power to Provide the DownwardReserve: Figs. 6–8 illustrate an example of how wind providesthe downward reserve in one simulation day. Fig. 6 showsthe reserve allocation between conventional units and wind inthe DAUC. For example, during the third 15-min interval, thedownward reserve requirement is 22 MW. The allocation inFig. 6 shows that wind power is expected to provide 11.26 MWof downward reserve while coal-fired generation is expectedto provide 10.74 MW. Downward reserve provided by windpower is executed by wind power curtailment. We can see thatthere are many periods in which wind power is expected toprovide the downward reserve. Fig. 7 provides the load forecasterror for the day, which shows that the downward reserve isrequired in time intervals 21 and 22, as the real load is smallerthan the forecast load. As wind power is expected to providethe downward reserve for those periods, as shown in Fig. 6,wind curtailments do occur in those periods as shown in Fig. 8.

Possibilities for Wind Power to Provide the Upward Re-serve: In DAUC, the lower bound of the 100% wind power


Fig. 7. Load forecast error curve for the simulation day.

Fig. 8. Wind power curtailment for the simulation day.

Fig. 9. Upward spinning reserve allocation in DAUC.

forecast probability interval provides the minimum wind powerfor each period of the next day. When the dispatched windpower is smaller than the lower bound of the forecast interval,the difference between the dispatched wind power and the lowerbound, which would otherwise be curtailed, can be used as up-ward reserve in UC.Figs. 9 and 10 illustrate one example of a case where wind

provides the upward reserve. The load forecast error curve isthe same as that shown in Fig. 7, which shows that the upwardreserve is needed in all periods except in periods 21 and 22. Aswe see in Fig. 10, wind power provides a portion of the reserverequirements in many of these periods.Table VI compares the system performance indices when

wind is taken as reserve provider (Case C**) and when it is not(Case C*).

Fig. 10. Upward spinning reserve allocation in real time economic dispatch.

TABLE VIIMPACT OF WHETHER TO TAKE WIND AS RESERVE PROVIDER ON SYSTEM

OPERATION COSTS

We see that, when wind power is taken as the reserve providerin DAUC, and declines, which indicates better systemeconomics and emission reduction.

V. CONCLUSION

This paper studies day-ahead unit commitment in wind-coalintensive power systems with special attention to achievingwind power benefits. Wind power is decomposed into twoparts, i.e., variability and uncertainty, based on the wind powerforecast. The impact of wind power variability and windpower uncertainty on the DAUC were studied separately.Different wind power dispatch priorities and the possibility ofthe spinning reserve provision by wind power are modeled inthe UC. Optimal wind power dispatch and spinning reserveprocurement strategies were obtained. A simulation systemcharacterizing the typical features of coal-intensive powersystems like those in China were used in the simulation study.With the wind power decomposition and the correspondingUC studies, the impact of wind power on UC is presented withmore clarity. The study’s main conclusions are as follows:1) More attention should be given to achieving wind powerbenefits when dispatching wind power in wind-coal in-tensive power systems. Due to the long start-up time,high start-up costs and high minimum stable output ofcoal-fired generators, they do not provide compatibleconditions for accommodating wind power. Thoughwind power itself is emission and fuel free, the negativeimpacts it has on coal-fired generator emission and fuelconsumption may greatly undermine the wind powerbenefits if wind generation and coal-fired generation arenot coordinated properly.

2) In wind-coal intensive power systems, the use of privi-leged wind power dispatch, in which wind curtailmentis allowed as long as wind power benefits are enhanced,can lead to the achievement of better wind power ben-efits than guaranteed wind power dispatch. In manypower systems, wind power curtailment is only resorted


TABLE VIIPARAMETERS OF THE 9 SELECTED UNITS FROM THE IEEE RTS 96 SYSTEM

to when system security is threatened. But where windpower benefits are concerned, wind curtailment shouldbe taken as a control option. It greatly enhances windpower benefits in wind-coal intensive power systems.

3) When wind power participates in the DAUC, procuringextra upward spinning reserve according to wind powerforecast error statistics while not procuring extra down-ward spinning reserve is a good spinning reserve pro-curement strategy. More downward reserve is expectedto result in a higher wind energy use rate and there-fore more fuel savings and emission reduction. But italso increases fuel consumption and emissions on thecoal-fired generator side when the coal fired generatoris reconfigured to provide the additional downward re-serve needed.

4) Taking wind power curtailment as a control option andconsidering wind power as a spinning reserve providerwhen procuring the spinning reserve in DAUC improvessystem economies and emission reduction.

APPENDIX A

Table VII lists the paramters of the 9 selected units from theIEEE RTS 96 system.

APPENDIX B

Constraints in the UC model:1) System power balance

where is available wind power during period ,is system load during period .

2) Generating capacity constraint

where is minimum output of unit , ismaximum output of unit ;

3) Ramp rate constraint

4) Wind curtailment constraint

5) Unit startup/shut down

6) Minimum up/down time

where

number of period unit must be initially online dueto its minimum up time constraint;minimum up time of unit ;

number of period unit has been online prior to thefirst period of the time span;initial commitment state of unit (1 if it is online, 0otherwise);number of period unit must be initially offline dueto its minimum downtime constraint;minimum down time of unit ;

number of period unit has been offline prior to thefirst period of the time span.

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Caixia Wang (S’10) received the B.Sc. and Ph.D.degrees in electrical engineering from North ChinaElectric Power University, Hebei Province, and Ts-inghua University, Beijing, China, in 2006 and 2012,respectively.She is now with State Grid Energy Research In-

stitute, Beijing, China. Her research interest is powersystem operation with wind power.

Zongxiang Lu (M’02) received the B.S. and Ph.D.degrees in electrical engineering from TsinghuaUniversity, Beijing, China, in 1998 and 2002,respectively.He is now an Associate Professor of Electrical En-

gineering at Tsinghua University, where he has beenemployed since 2002. His research interests includepower system reliability, renewable energy and mi-crogrid, and large scale wind power integration.

Ying Qiao received the B.S. and Ph.D. degrees inelectrical engineering from Shanghai Jiaotong Un-verisity, Shanghai, China, and Tsinghua University,Beijing, China, in 2002 and 2008, respectively.She is now a lecturer of Electrical Engineering at

Tsinghua University, where she has been employedsince 2010. Her research interests include renewableenergy and power system security and control.

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