电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2014年
20期
9-17
,共9页
风力发电%储能系统%荷电状态%偏差控制%功率预测%时间尺度
風力髮電%儲能繫統%荷電狀態%偏差控製%功率預測%時間呎度
풍력발전%저능계통%하전상태%편차공제%공솔예측%시간척도
wind power generation%energy storage system ESS%state of charge SOC%deviation control%power prediction%time scale
提出了一种新型的基于风电功率预测偏差和电池荷电状态(SOC)反馈的储能系统控制策略，通过预测结果计算风电功率的变化偏差，得出完全补偿波动所需的储能系统充放电功率，引入补偿系数联合求解获得储能系统的充放电控制指令。同时，建立了补偿系数的动态优化模型，包括长时间尺度下基于输出功率波动和电池容量变化指标的基准补偿系数寻优模型，短时间尺度下基于电池 SOC 指标和充放电状态的补偿系数快速修正模型。算法采用的最优求解和 SOC 指标具有广泛的适应性，便于推广不同容量储能系统在风电功率平滑中的应用，可以兼顾储能电池的寿命和输出功率的平滑性。算例结合风电场的功率实测数据，进行储能系统配置仿真，验证了该控制策略能够最大程度发挥储能系统能力，在维持电池能量稳定前提下，平抑风电场输出功率的波动。
提齣瞭一種新型的基于風電功率預測偏差和電池荷電狀態(SOC)反饋的儲能繫統控製策略，通過預測結果計算風電功率的變化偏差，得齣完全補償波動所需的儲能繫統充放電功率，引入補償繫數聯閤求解穫得儲能繫統的充放電控製指令。同時，建立瞭補償繫數的動態優化模型，包括長時間呎度下基于輸齣功率波動和電池容量變化指標的基準補償繫數尋優模型，短時間呎度下基于電池 SOC 指標和充放電狀態的補償繫數快速脩正模型。算法採用的最優求解和 SOC 指標具有廣汎的適應性，便于推廣不同容量儲能繫統在風電功率平滑中的應用，可以兼顧儲能電池的壽命和輸齣功率的平滑性。算例結閤風電場的功率實測數據，進行儲能繫統配置倣真，驗證瞭該控製策略能夠最大程度髮揮儲能繫統能力，在維持電池能量穩定前提下，平抑風電場輸齣功率的波動。
제출료일충신형적기우풍전공솔예측편차화전지하전상태(SOC)반궤적저능계통공제책략，통과예측결과계산풍전공솔적변화편차，득출완전보상파동소수적저능계통충방전공솔，인입보상계수연합구해획득저능계통적충방전공제지령。동시，건립료보상계수적동태우화모형，포괄장시간척도하기우수출공솔파동화전지용량변화지표적기준보상계수심우모형，단시간척도하기우전지 SOC 지표화충방전상태적보상계수쾌속수정모형。산법채용적최우구해화 SOC 지표구유엄범적괄응성，편우추엄불동용량저능계통재풍전공솔평활중적응용，가이겸고저능전지적수명화수출공솔적평활성。산례결합풍전장적공솔실측수거，진행저능계통배치방진，험증료해공제책략능구최대정도발휘저능계통능력，재유지전지능량은정전제하，평억풍전장수출공솔적파동。
A new control strategy of energy storage systems ESSs based on wind power prediction deviation and battery state of charge SOC feedback is proposed.The deviation of wind power variation is calculated through prediction results to get the charge-discharge power of ESSs needed by totally compensating fluctuation.The charge-discharge power orders are then obtained by introducing the compensation factor in the joint solution. Moreover, a dynamic optimizing model of the compensation factor is developed, including the standard compensation factor optimizing model based on output power fluctuation and battery capacity changing value and the compensation factor fast-modification model based on battery SOC and charge-discharge status under short-time scale.The optimal solution and SOC value used in the proposed algorithm have a high adaptation level,which can generalize ESSs of different capacities in the application of wind power smoothing and give consideration to the lifetime of battery and smoothness of wind power.Finally,a case study is made that describes simulations with the historical power data on wind farm and ESSs configuration taken into account.The results have proved that the control strategy is able to develop the capacity of ESSs to the full and reduce the fluctuation of wind farm power on the premise that the energy capacity of battery is maintained stable.
