基于可逆固体氧化物电池的风光氢综合能源系统容量规划

doi:10.11930/j.issn.1004-9649.202211106

摘要/Abstract

摘要：

可逆固体氧化物电池（reversible solid oxide cell，RSOC）作为新型氢储能技术，有利于促进可再生能源消纳、提高系统运行效率。为此，提出一种基于RSOC技术的风光氢综合能源系统规划设计方法。首先，建立风光氢综合能源系统规划模型，考虑RSOC辅助系统（balance of plant，BOP）功耗占比高、功率调节受限等约束。其次，以系统年弃电缺电量、投资成本最小化为目标，采用粒子群优化算法求解该规划问题。最后，针对氢气价格、RSOC成本等不确定性因素，开展系统规划灵敏度分析。仿真结果表明该方法能够获得合理的配置方案，大规模减小系统弃电缺电频率，提升系统资源配置的灵活性。

关键词: 可逆固体氧化物电池, 氢储能, 综合能源系统, 容量规划, 规划灵敏度分析

Abstract:

As a new energy storage technology, reversible solid oxide cell (RSOC) can promote the renewable energy consumption and improve the system efficiency. Therefore, a capacity planning method of an integrated energy system of wind photovoltaic and hydrogen based on RSOC is proposed. Firstly, the planning model of the integrated energy system of wind photovoltaic and hydrogen is established, considering the constraints of the high energy consumption of the balance of plant (BOP) system and the limited power regulation of the RSOC system. Secondly, the particle swarm optimization (PSO) algorithm is used to solve this planning problem, aiming at minimizing the annual redundant and lacking power, and investment cost. Finally, the system planning sensitivity analysis is performed for the uncertain factors of the RSOC cost and hydrogen price. The simulation results show that the proposed method can obtain a reasonable configuration scheme, greatly reducing the redundant and lacking power and improving the flexibility of the system resource allocation.

Key words: reversible solid oxide cell, hydrogen energy storage, integrated energy system, capacity planning, planning sensitivity analysis

窦真兰, 袁本峰, 张春雁, 肖国萍, 王建强. 基于可逆固体氧化物电池的风光氢综合能源系统容量规划[J]. 中国电力, 2023, 56(10): 22-32.

Zhenlan DOU, Benfeng YUAN, Chunyan ZHANG, Guoping XIAO, Jianqiang WANG. Capacity Planning of Integrated Energy System of Wind Photovoltaic and Hydrogen Based on Reversible Solid Oxide Cell[J]. Electric Power, 2023, 56(10): 22-32.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202211106

https://www.electricpower.com.cn/CN/Y2023/V56/I10/22

图/表 18

图 1 RSOC系统流程

Fig.1 RSOC system flow diagram

图 2 基于RSOC的风光氢综合能源系统示意

Fig.2 Schematic diagram of the integrated energy system of wind photovoltaic and hydrogen based on RSOC system

图 3 PSO算法求解流程

Fig.3 Solution flow chart of PSO algorithm

图 4 风速、光照强度、负载日分布曲线

Fig.4 One-day profiles of wind velocity, solar radiation and load

表 1 不同季节的平均风速、光照强度和负载负荷分布[22]

Table 1 The average wind speed, global irradiance and load in four seasons[22]

季节	风速/(m·s^–1)	辐照强度/(W·m^–2)	负载负荷/kW
春季	6.31	193.5	643
夏季	5.10	337.3	651
秋季	5.53	311.2	636
冬季	7.30	163.5	580

表 2 设备投资成本[22]

Table 2 The capital cost of each unit[22]

设备	投资成本	维护成本	更新成本	寿命/年
风机	7 250/(元·kW^–1)	580/(元·(kW·年)^–1)	—	20
光伏	7 000/(元·kW^–1)	560/(元·(kW·年)^–1)	—	20
RSOC	16 244/(元·kW^–1)	650/(元·(kW·年)^–1)	4 873/(元·kW^–1)	5
储氢罐	15 000/(元·kg^–1)	450/ (元·(kg·年)^–1)	8 000/(元·kg^–1)	5

表 3 传统燃煤发电排污相关参数[27]

Table 3 The related parameters of the pollutant discharge of the traditional coal-fired power generation[27]

污染物种类	排放量/ (g·(kW·h)^–1)	环境价值/ (元·kg^–1)	惩罚数量级/ (元·kg^–1)
CO₂	86.4725	0.02275	0.01768
SO₂	0.1083~3.9446	5.9995	4.6501
NO_x	0.1547~3.0938	7.995	6.1997

表 4 规划模型输入参数

Table 4 Input parameters of the planning model

模型参数	数值	模型参数	数值
K_pu	0.0000668	P_SOEC,max/kW	6 000
K_vg	0.4496	P_SOFC,min/kW	60
$K_{\rm eh,h_2o} $	0.0383	P_SOFC,max/kW	3 000
K_eh,air	0.0374	U_SOEC,min/kW	600
$K_{\rm cp,h_2} $	0.1973	U_SOEC,max/kW	600
K_cp,air	0.1364	P_tank,min/MPa	20
P_SOEC,min/kW	120	P_tank,max/MPa	45

表 5 系统最优配置容量

Table 5 The optimal capacity of each unit

设备配置容量		数值
风力发电机组额定功率/kW		727
光伏阵列额定功率/kW		1 231
RSOC系统额定功率/kW		792
储氢罐体积/m³		17

图 5 可再生能源出力分布

Fig.5 The output distribution of the renewable energy

图 6 系统弃电缺电分布

Fig.6 The redundant and lacking power distributions of the system

表 6 有无RSOC的综合能源系统源-荷匹配性比较

Table 6 Comparison of the source-load matching with and without the RSOC system

系统	年弃电缺电量/(MW·h)	η_mis/%	年风光消纳率/%
含RSOC氢电转换	440	8	96
不含RSOC氢电转换	5 722	102	49

图 7 RSOC系统出力分布

Fig.7 The output distribution of RSOC system

图 8 储氢罐压力分布

Fig.8 The pressure distribution of the hydrogen storage tank

图 9 氢气价格对容量配置结果的影响

Fig.9 The effect of the hydrogen price on the capacity configuration

图 10 氢气价格对优化目标结果的影响

Fig.10 The effect of the hydrogen price on the optimization objective

图 11 RSOC成本对容量配置结果的影响

Fig.11 The effect of the RSOC cost on the capacity configuration

图 12 RSOC成本对优化目标结果的影响

Fig.12 The effect of the RSOC cost on the optimization objective

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