Dual-objective optimization of energy networks with shared energy storage based on Nash bargaining

doi:10.3969/j.issn.2097-0706.2022.07.005

Abstract

Abstract:

The construction of energy networks has become the pillar of new power systems and the incentive to large-scale development of renewable energy,which facilitates the realization of carbon peaking and carbon neutrality. There are problems of poor techno-economic performances and low adaptability in the application of independent energy storage technology in energy networks. Thus,a dual-objective optimization on the benefits of shared energy storage and energy costs of energy networks is proposed. To cope with the unbalanced profit allocation between distributed cold, heating and power systems in an energy network, Nash bargaining is introduced to improve the allocation. A case study is made on an energy network composed of one shared energy storage system（SESS）and four multi-distributed energy systems（MDESs）. The study results show that the benefits of the shared energy storage system and the non-inferior solution for the operation costs of the MDESs have been improved with the increase of the shared energy storage capacity, but the room for non-inferior solution improvement is shrinking. Nash bargaining make the cost reduction allocated to the distributed cold, heating and power systems more evenly, which ensures the users' profits and encourages them to participate into the energy storage. But due to the constraints on the user's operating costs brought by Nash bargaining, the benefits of shared energy storage and operation costs of the MDES deteriorate overall.

Key words: carbon neutrality, new power system, energy network, shared energy storage system, renewable energy, dual-objective optimization, distributed energy, Nash bargaining

CLC Number:

TK018：TM73

YE Zhaonian, ZHAO Changlu, WANG Yongzhen, HAN Kai, LIU Chaofan, HAN Juntao. Dual-objective optimization of energy networks with shared energy storage based on Nash bargaining[J]. Integrated Intelligent Energy, 2022, 44(7): 40-48.

Figures/Tables 16

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Table 1

Constraints on equipment of the MDES

名称	约束	变量说明
热电联产机组	$P C H P, e i m i n ≤ P C H P, e i t ≤ P C H P, e i m a x P C H P, h i t = (1 - η C H P, e i - η C H P, l o s s i) η C H P, h i η C H P, e i P C H P, e i t - λ C H P, e i m a x Δ t ≤ P C H P, e i t + 1 - P C H P, e i t ≤ λ C H P, e i m a x Δ t$	$P C H P, e i t$ 为电出力; $P C H P, h i t$ 为热出力; $η C H P, e i$ 为发电效率; $η C H P, l o s s i$ 为热损失效率; $η C H P, h i$ 为制热系数; $λ C H P, e i m a x$ 为爬坡率上限
电锅炉机组	$P E B, h i t = η E B P E B, e i t P E B, h i m i n ≤ P E B, h i t ≤ P E B, h i m a x$	$P E B, h i t$ 为热出力; $η E B$ 为制热效率; $P E B, e i t$ 为耗电功率
吸收式制冷机组	$P A C, c i t = C O P P A C, h i t P A C, c i m i n ≤ P A C, c i t ≤ P A C, c i m a x$	$P A C, c i t$ 为冷出力; $P A C, h i t$ 为耗热功率; $C O P$ 为制冷性能系数
电压缩式制冷机组	$P E C, c i t = η E C P E C, e i t P E C, c i m i n ≤ P E C, c i t ≤ P E C, c i m a x$	$P E C, c i t$ 为冷出力; $P E C, e i t$ 为耗电功率; $η E C$ 为制冷效率
电热冷平衡	$P C H P, e i t + P P V i t + P E G i t = P E B, e i t + P E C, e i t + P l o a d, e i t P C H P, h i t + P E B, h i t = P A C, h i t + P l o a d, h i t P A C, c i t + P E C, c i t = P l o a d, c i t$	$P P V i t$ 为光伏电出力; $P E G i t$ 为电网购电量; $P l o a d, e i t$ 为电负荷; $P l o a d, h i t$ 为热负荷; $P l o a d, c i t$ 为冷负荷
加入共享储能后电平衡	$P C H P, e i t + P P V i t + P S E S S, d i t + P E G i t + ∑ j ≠ i n P i, j t = P E B, e i t + P E C, e i t + P S E S S, c i t + P l o a d, e i t$	$P S E S S, c i t$ , $P S E S S, d i t$ 为t时刻SESS的总充、放电功率

Table 1

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参数	数值
共享储能系统单位功率租赁费用/(元·kW^-1)	0.28
共享储能系统单位功率成本/(元·kW^-1)	1 000
共享储能系统单位容量成本/[元·(kW·h)^-1]	1 100
共享储能系统运营周期/a	8
共享储能系统功率上限与容量上限的比例系数	0.20
CHP机组发电效率	0.35
CHP机组散热损失率	0.15
EB制热效率	0.95
AC机组制冷系数	1.50
EC机组制冷效率	2.50
天然气单价/(元·m^-3)	2.54
CHP机组单位规模建设成本/(元·kW^-1)	3 200
EB机组单位规模建设成本/(元·kW^-1)	1 200
AC机组单位规模建设成本/(元·kW^-1)	1 200
EC机组单位规模建设成本/(元·kW^-1)	1 080
PV机组单位规模建设成本/(元·kW^-1)	2 400
设备运营周期/a	20
利率	0.05
维护成本与建设成本之比	0.02

MDESs	CHP	EB	AC	EC	PV
MDES1	1 500	300	1 100	300	1 100
MDES2	1 200	600	1 600	700	800
MDES3	600	400	1 200	1 000	600
MDES4	900	600	1 500	900	1 000