Data-driven reactive power optimization algorithm for the distribution network with high proportion of renewable energy

doi:10.3969/j.issn.2097-0706.2023.11.002

Abstract

Abstract:

With the integration of massive distributed new energy into distribution networks， power loss and voltage deviation at nodes are becoming increasingly severe. The high requirements on high-proportion renewable energy distribution networks' adjustability can not be satisfied by traditional measures merely，such as installation of reactive power compensation devices， adjusting the voltage at the generator side. Therefore，the reactive power regulation capacities of different types of new energy generators in distribution networks are study deeply. The study analyses the objective function and constraint settings，and outlines a data-driven reactive power regulation algorithm. The algorithm can regulate node voltage and reduce power loss of the distribution network at the same time. Firstly，a mathematical model of reactive power optimization for the high-proportion new energy distribution network is constructed， and solved by various intelligent algorithms. Subsequently，the reactive power regulation solution sets obtained from the algorithms are used as training data for the deep learning long-short-term memory（LSTM）network. The trained network can predict reactive power regulation strategies efficiently based on the model above. Finally，the effectiveness and optimization performance of the proposed algorithm is validated by in an IEEE 14-bus system and an IEEE 33-bus system.

Key words: high-penetration new energy, distribution network, deep learning, reactive power optimization, Pareto front

CLC Number:

TK01

LIN Honghong, YU Tao, ZHANG Guiyuan, ZHANG Xiaoshun. Data-driven reactive power optimization algorithm for the distribution network with high proportion of renewable energy[J]. Integrated Intelligent Energy, 2023, 45(11): 10-19.

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新能源	接入新能源序号	风速/（m⋅s^-1）	辐照度/(W⋅m^-2)	有功功率/kW	无功功率范围/(kV·A)
光伏电站	1		775.43	54.28	[-25.35,25.35]
光伏电站	2		677.71	47.44	[-36.73,36.73]
风电场	1	10.18		239.30	[-110.39,133.64]
电动汽车充放电站	1			70.80	[-70.62,70.62]

新能源	接入新能源序号	风速/（m⋅s^-1）	辐照度/(W⋅m^-2)	有功功率/kW	无功功率范围/(kV·A)
光伏电站	1		589.57	41.27	[-43.55,43.55]
	2		578.71	40.51	[-44.26,44.26]
	3		535.71	37.50	[-46.84,46.84]
	4		515.00	36.05	[-47.96,47.96]
风电场	1	11.70		290.10	[-76.50,111.07]
	2	11.48		282.74	[-81.41,114.34]
	3	11.36		278.64	[-84.15,116.16]
电动汽车充放电站	1			70.00	[-71.41,71.41]
	2			69.08	[-72.30,72.30]
	3			63.12	[-77.56,77.56]