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Analysis of Emergency Demand Response Levels of Central Air-Conditioning
Xianjun Qi,Zongshuo Ji,Hongbin Wu,Jingjing Zhang,Hejun Yang 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.6
Central air-conditioning (CAC) is a fl exible load which can be dispatched during an emergency demand response (EDR) program. However, consumers’ trade-off between thermal comfort levels (TCLs) and profi ts will aff ect the potential of CAC. Therefore, this paper proposes a method to evaluate CAC’S response levels. An EDR optimization model simulating consumers’ trade-off between TCLs and profi ts is established and it is solved by a particle swarm optimization (PSO) algorithm. Then the defi nition of EDR levels is presented to quantitatively analyze the capability of CAC providing the EDR. Furthermore, uncertainty of EDR levels caused by stochastic initial indoor temperature is analyzed through a Monte Carlo (MC) simulation. A case study shows the rationality of the presented method, and the eff ects of weight coeffi cients, compensation prices and penalty prices on EDR levels are also analyzed.
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Research on Large‑scale Photovoltaic Planning Based on Risk Assessment in Distribution Network
Lei Wang,Minyu Yuan,Fan Zhang,Xuli Wang,Jing Ma,Lei Dai,Xianjun Qi,Rui Bi 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.3
Risks caused by large amounts of distributed photovoltaic (PV) feeding into distribution networks, have an impact on PV planning, which has become a critical consideration for distribution networks’ operation. In this paper, a large-scale PV planning method is proposed which based on risk assessment in distribution networks. Cluster division is used to group large-scale distributed PVs. A risk assessment is performed on the distribution network, considering the correlation between PVs and loads. The efects of load fuctuations, PV quantity, capacity and location on the operational risk of the distribution network are analyzed and discussed. A large-scale PV planning model is established with the goal of maximizing the comprehensive benefts, considering the penalty cost of node voltage over-limit and branch power fow over-limit risk. Finally, the genetic algorithm is used to solve the planning model. The simulation results demonstrate the efectiveness of the proposed method.
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