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Energy efficiency evaluation and optimization of active distribution networks with building integrated photovoltaic systems

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  • Luo, Tengqi
  • Xuan, Ang
  • Wang, Yafei
  • Li, Guanglei
  • Fang, Juan
  • Liu, Zhengguang

Abstract

With the rapid development of building integrated photovoltaic (BIPV) technology, rooftop PV grid-connected systems face challenges in operation. When the consumption rate of BIPV systems is low, power reverse increases distribution network losses and decreases power supply quality. Traditional energy efficiency evaluations for distribution networks do not consider the impact of low BIPV consumption rates on network losses. This paper establishes an energy efficiency evaluation model for distribution networks with BIPV systems based on adversarial interpretive structural modeling and proposes an energy efficiency indicator system applicable to distribution networks with BIPV systems. The method was applied to eight distribution networks with BIPV systems, achieving accurate energy efficiency level rankings. Through single-factor sensitivity analysis of the indicator system, the primary factors affecting distribution networks with BIPV systems energy efficiency were identified. A reactive power optimization model based on multi-objective particle swarm optimization algorithm was established. After optimization, network losses decreased by 153 kW, PV consumption rate increased by 73 %, and node voltage drift was significantly enhanced. Corresponding loss reduction strategies were proposed for other indicators. This paper provides valuable references for planning and renovating distribution networks with BIPV systems.

Suggested Citation

  • Luo, Tengqi & Xuan, Ang & Wang, Yafei & Li, Guanglei & Fang, Juan & Liu, Zhengguang, 2023. "Energy efficiency evaluation and optimization of active distribution networks with building integrated photovoltaic systems," Renewable Energy, Elsevier, vol. 219(P1).
  • Handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123013629
    DOI: 10.1016/j.renene.2023.119447
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