电网技术
電網技術
전망기술
POWER SYSTEM TECHNOLOGY
2013年
5期
1311-1316
,共6页
风电并网%旋转备用%时变可靠性%成本效益分析%随机规划%粒子群算法
風電併網%鏇轉備用%時變可靠性%成本效益分析%隨機規劃%粒子群算法
풍전병망%선전비용%시변가고성%성본효익분석%수궤규화%입자군산법
grid-connected wind farms%spinning reserve%time-varying reliability%cost-benefit analysis%stochastic programming%particle swarm optimization
大规模风电并网后,系统运行经济性和可靠性之间的矛盾十分突出,传统确定旋转备用的方法存在较大的局限性。建立的含风系统旋转备用随机规划模型,能够根据系统容量冗余度,灵活分配各时段可靠性权重,实现调度周期内可靠性的协调优化。该模型充分考虑不同机组提供旋转备用的成本差异,允许机组对旋转备用进行报价,以发电成本、直接备用成本和期望停电成本三者之和最小为目标,实现发电侧和用户侧整体经济效益的最大化。应用该模型,可以对含风系统的旋转备用进行成本效益分析,为调度机构设置合理的可靠性水平提供决策依据。采用粒子群算法对模型进行求解,并通过算例分析验证了上述模型和算法的有效性。
大規模風電併網後,繫統運行經濟性和可靠性之間的矛盾十分突齣,傳統確定鏇轉備用的方法存在較大的跼限性。建立的含風繫統鏇轉備用隨機規劃模型,能夠根據繫統容量冗餘度,靈活分配各時段可靠性權重,實現調度週期內可靠性的協調優化。該模型充分攷慮不同機組提供鏇轉備用的成本差異,允許機組對鏇轉備用進行報價,以髮電成本、直接備用成本和期望停電成本三者之和最小為目標,實現髮電側和用戶側整體經濟效益的最大化。應用該模型,可以對含風繫統的鏇轉備用進行成本效益分析,為調度機構設置閤理的可靠性水平提供決策依據。採用粒子群算法對模型進行求解,併通過算例分析驗證瞭上述模型和算法的有效性。
대규모풍전병망후,계통운행경제성화가고성지간적모순십분돌출,전통학정선전비용적방법존재교대적국한성。건립적함풍계통선전비용수궤규화모형,능구근거계통용량용여도,령활분배각시단가고성권중,실현조도주기내가고성적협조우화。해모형충분고필불동궤조제공선전비용적성본차이,윤허궤조대선전비용진행보개,이발전성본、직접비용성본화기망정전성본삼자지화최소위목표,실현발전측화용호측정체경제효익적최대화。응용해모형,가이대함풍계통적선전비용진행성본효익분석,위조도궤구설치합리적가고성수평제공결책의거。채용입자군산법대모형진행구해,병통과산례분석험증료상술모형화산법적유효성。
After large-scale wind farms are connected with the grid, conspicuous contradiction between economy and reliability of power grid operation appears due to the limitation of traditional method determining spinning reserve. A stochastic programming model for spinning reserve of power grid connected with large-scale wind farms is built, which can flexibly allocate reliability weights in different time-intervals to implement the coordinated optimization of reliability within dispatching period. Fully considering cost differences among spinning reserves provided by different units, the built model permits units to bid prices of spinning reserves, and the minimization of generation cost, spinning reserve cost, and expected outage cost is taken as objective function to implement the maximization of whole economic benefits at generation side and consumer side. The built model can be applied to perform cost-benefit analysis for power grid containing wind farms and to provide decision-making foundation for dispatching departments to set reasonable reliability level. The built model is solved by particle swarm optimization (PSO) algorithm, and the effectiveness of above-mentioned model and algorithm is verified by simulation results of a 10-machine system.