• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

Electric Power Construction ›› 2016, Vol. 37 ›› Issue (9): 14-.doi: 10.3969/j.issn.1000-7229.2016.09.002

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Operation Strategy for Residential Quarter Energy Hub Considering Energy Demands Uncertaintie

ZHANG Huayi1, WEN Fushuan1,2, ZHANG Can3,WANG Peng1, MENG Jinling4, LIN Guoying4   

  1. 1.School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China; 2. Department of Electrical and Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei; 3. State Grid Nanjing Power Supply Company,Nanjing 210019, China; 4. Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
  • Online:2016-09-01
  • Supported by:
    Project supported by the National Basic Research Program of China (973 Program) (2013CB228202); National Natural Science Foundation of China (51477151)

Abstract: In recent years, the popularization of combined heat and power generation and electric heating has attracted extensive attention. The main energy demands in a residential quarter are heating demands and electricity demands, and the energy hub can be used to descript the coupling relationship between the energy demand and the energy input. Given this background, this paper firstly presents a mathematical model for the residential quarter energy hub, with the combined heat and power generation and the heat pump as energy devices. Then, this paper constructs the deterministic model of the residential quarter energy hub operation optimization, and considers the charging load of electrical vehicles as a controllable load to participate in the operation optimization. Energy demands of a residential quarter are uncertain, and various decision-makers may have different risk preferences in determining optimal operation strategies. With this consideration, this paper employs the information gap decision theory (IGDT) to develop the robust optimization model and the opportune-windfalling model respectively, in order to obtain the scheduling strategy of risk-aversion decision-makers and risk-preference decision-makers. And then, this paper constructs the mixed integer linear programming model and adopts the CPLEX to solve the model. Finally, a residential quarter is employed to demonstrate the essential characteristics of the developed model and method.

Key words: residential quarter energy hub, electric vehicle charging, information gap decision theory (IGDT), robust optimization model, opportune-windfalling model

CLC Number: