Bi-level Optimal Operation Strategy of Energy Storage with Large-scale New Energy System under the Participation of Virtual Power Plant

doi:10.11985/2020.02.004

Abstract

Abstract:

In response to the flexible operation scheduling of the energy storage of large-scale new energy system, a bi-level optimal model with the participation of virtual power plant (VPP) is proposed. Weibull, Beta and Gumble distribution are used to describe the uncertainty of wind, PV and hydropower, and the overestimation and underestimation cost of new energy output are considered. Introducing VPP to improve the flexibility, the model takes VPP as an independent market subject to participate in scheduling, and solves the problem alternately between the two levels to achieve collaborative optimization. According to the characteristics of mixed integer, nonconvex, nonlinear and multi-objective, a novel multi group pseudo parallel multi-objective algorithm is proposed to solve the problem. The modified IEEE39 bus system is used as an example to verify the model, it can balance the market entities at all levels, ensure the safe operation of the system and maximize the operating profit, and effectively realize the sustainable development of the power system. The effectiveness and competitiveness of the algorithm are verified simultaneously.

Key words: Large-scale new energy, virtual power plant, energy storage, bi-level optimization, multi-objective algorithm

CLC Number:

TM41

WANG Kaike, NAN Dongliang, LI Yong, ZHANG Lu, LI Xiaozhu. Bi-level Optimal Operation Strategy of Energy Storage with Large-scale New Energy System under the Participation of Virtual Power Plant[J]. Journal of Electrical Engineering, 2020, 15(2): 24-33.

Figures/Tables 16

References 15

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测试函数	多种群伪并行算法	NSGA-Ⅱ	MOEA/D
ZDT1	1.313×10^-1	5.070×10^-1	2.634×10^-1
ZDT2	1.287×10^-1	4.831×10^-1	1.266×10^-1
ZDT3	4.614×10^-1	5.881×10^-1	4.694×10^-1
ZDT6	1.254×10^-1	—	2.361×10^-1
SCH	1.402×10^-1	2.862×10^-1	1.783×10^-1
DTLZ2	3.289×10^-1	8.246×10^-1	4.432×10^-1
DTLZ3	4.870×10^-1	—	5.176×10^-1
DTLZ4	2.239×10^-1	7.749×10^-1	3.412×10^-1

惩罚成本系数	风电		光伏		水电
惩罚成本系数	K_PW	K_RW	K_PPV	K_RPV	K_PR	K_RR
数值	60	110	85	100	70	105

名称	参数	VPP	名称	参数	VPP
RL	RL型负荷占比(%)	25	TL	TL型负荷占比(%)	35
	$Lim_{{\rm{i}},{\rm{max}}}^{{\rm{RL}}}$	10		$P_{{\rm{TL}}i}^{\rm{u}}{\rm{/p}}.{\rm{u}}.$	0.5
	$T_{{\rm{max}}}^{{\rm{RL}}}$	5		$P_{{\rm{TL}}i}^{\rm{l}}{\rm{/p}}.{\rm{u}}.$	0.5
	$T_{{\rm{min}}}^{{\rm{RL}}}$	3		$P_{{\rm{TL}}i}^{{\rm{max}}}{\rm{/p}}.{\rm{u}}.$	0.8
	调用成本/($/kWh)	2		调用成本/($/kWh)	0.8

	上界/MW	下界/MW	爬坡/MW	停启费用/($/MW)	额定功率/MW
常规1	55	10	20	20 000	—
常规2	40	10	20	20 000	—
常规3	40	10	20	15 000	—
风电	—	—	—	—	850
光伏	—	—	—	—	450
水电	—	—	—	—	50
联络线	100	400	100	—	—

	a_i	b_i	c_i	d_i	e_i
机组1	1 455.605 6	39.580 4	0.109 0	270	0.098
机组2	1 469.402 6	40.540 7	0.129 5	380	0.094
机组3	1 469.402 6	40.540 7	0.129 5	380	0.094