考虑多重不确定性的多站融合容量优化配置方法

doi:10.3969/j.issn.2097-0706.2022.01.005

摘要/Abstract

摘要：

多站融合中太阳能、风能等可再生能源以及负荷需求具有不确定性,使多站融合规划需要考虑更多不确定性因素。为有效提高多站融合建设的经济性,在保证系统供电可靠性和新能源消纳的同时,建立以平准化能源成本为优化目标的多站融合容量优化配置策略。在量子引力搜索算法的基础上引入莱维飞行以进一步提高搜索能力,在算法中利用蒙特卡洛模拟生成随机参数,从而求解包含多重不确定性的容量配置问题。以某地多站融合数据为例进行仿真分析,并与传统的粒子群算法以及未改进的量子引力搜索算法进行对比,算例结果表明所提方法提高了容量配置问题的求解精度和稳定性并能够有效降低多站融合的综合用电成本。

关键词: 多站融合, 量子引力搜索算法, 莱维飞行, 蒙特卡洛模拟, 可再生能源

Abstract:

The uncertainties in renewable energies,such as solar energy and wind power,and load demands make multi-station integration changeable.In order to effectively boost the economy of multi-station integration,on the premise of reliable power supply and new energy consumption of the power system, an optimal capacity configuration method for multi-station integration which takes levelized energy cost as the optimization objective is proposed.To solve the optimal capacity configuration considering multiple uncertainties,Lévy flight is introduced into it on the basis of quantum-inspired gravitational search algorithm to improve the search ability,and the random parameters are generated by Monte Carlo simulation.Taking a multi-station integration project as an example,the simulation analysis is compared with the traditional particle swarm algorithm and unimproved quantum-inspired gravitational search algorithm.The simulation results show that the proposed method improves the accuracy and stability of the solution for capacity allocation problem,and can effectively reduce the power consumption cost of multi-station integration.

Key words: multi-station integration, quantum-inspired gravitational search algorithm, Lévy flight, Monte Carlo simulation, renewable energy

中图分类号:

TK01⁺9:TM73

路晓敏, 张明, 邓星, 王立伟, 陶以彬, 胡安平. 考虑多重不确定性的多站融合容量优化配置方法[J]. 综合智慧能源, 2022, 44(1): 31-38.

LU Xiaomin, ZHANG Ming, DENG Xing, WANG Liwei, TAO Yibin, HU Anping. Optimal capacity configuration for multi-station integration considering multiple uncertainties[J]. Integrated Intelligent Energy, 2022, 44(1): 31-38.

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项目	单位	风力发电机	光伏电池	蓄电池
额定功率	kW	100	1	—
逆变器效率	%	90	97	96
额定电压	V	220	36	2
使用年限	年	20	20	10
单价	元/台	800 000	10 000	1 000

算法指标	LCOE/[元·（kW·h）^-1]	时间/s
LQGSA-MCS均值	0.79	9.53
LQGSA-MCS标准差	0.04	2.38
QGSA-MCS均值	0.81	10.07
QGSA-MCS标准差	0.05	1.56
PSO-MCS均值	0.90	10.89
PSO-MCS标准差	0.07	2.48