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Collaborative Optimal Configuration for Integrated Energy System Considering Uncertainties of Demand Response
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1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China;2.Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030000, China

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    Abstract:

    This paper proposes a method of equipment optimal configuration for an integrated energy system (IES) considering the uncertainties of integrated demand response (IDR). Firstly, in order to improve the efficiency of energy use, the basic structure of IES considering IDR is constructed based on a combined cooling, heating and power system. Then, the aleatory and epistemic uncertainty of IDR are analyzed by the evidence theory, and the load curve under a certain price scheme is optimized by using a credible level constraint. On this basis, a bi-level collaborative planning model considering the optimal configuration and operation strategy of the equipment in IES is established. In the upper level, the equipment selection and capacity allocation are conducted with the goal of minimizing the total planning cost. And in the lower level, the equipment output is optimized with the lowest operation cost as the objective. By comparing the total costs of all tariff schemes, the optimal tariff and equipment allocation scheme is obtained. Finally, the proposed approach is illustrated on an example and the results demonstrate that the optimal allocation results considering the uncertainties of IDR are more resistant to risks. Meanwhile, evidence theory can be used to achieve the unification of probability theory and interval theory.

    表 3 Table 3
    表 7 Table 7
    表 1 各场景优化配置结果及成本对比Table 1 Optimized configuration results and cost comparison for each case
    表 6 Table 6
    表 8 Table 8
    表 2 Table 2
    表 4 Table 4
    图1 IES能量流图Fig.1 Energy flow diagram of IES
    图1 IES能量流图Fig.1 Energy flow diagram of IES
    图2 优化负荷计算的示意图Fig.2 Schematic diagram for calculating optimized load
    图3 夏季14:00冷负荷的累积概率分布Fig.3 Cumulative probability distribution of cooling load at 14:00 in summer
    图4 不同情况下的累积概率分布Fig.4 Cumulative probability distribution underdifferent conditions
    图 计及IDR不确定性的IES优化配置模型求解流程Fig. Solution flow of IES optimal configuration model with IDR uncertainty
    图 IES协同规划框图Fig. Collaborative planning block diagram of IES
    图 计及IDR不确定性的IES优化配置模型求解流程Fig. Solution flow of IES optimal configuration model with IDR uncertainty
    图 夏季典型日负荷曲线Fig. Load curve for a typical day in summer
    图 春秋季典型日负荷曲线Fig. Load curve for typical spring and autumn days
    图 夏季典型日负荷曲线Fig. Load curve for a typical day in summer
    图 冬季典型日负荷曲线Fig. Load curve for a typical day in winter
    表 5 Table 5
    图 计及IDR前后负荷曲线对比Fig. Comparison of load curves before and after considering IDR
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LIU Wenxia,LI Zhengzhou,YANG Yue,et al.Collaborative Optimal Configuration for Integrated Energy System Considering Uncertainties of Demand Response[J].Automation of Electric Power Systems,2020,44(10):41-49.DOI:10.7500/AEPS20190731013

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History
  • Received:July 31,2019
  • Revised:November 04,2019
  • Adopted:
  • Online: May 22,2020
  • Published: