需求响应下的并网型风-光-沼微能源网优化配置

doi:10.16183/j.cnki.jsjtu.2022.017

上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (1): 10-16.doi: 10.16183/j.cnki.jsjtu.2022.017

所属专题：《上海交通大学学报》2023年“新型电力系统与综合能源”专题

• 新型电力系统与综合能源 • 上一篇下一篇

需求响应下的并网型风-光-沼微能源网优化配置

俞发强¹, 张名捷¹, 程语², 陈达伟², 杨函煜³(), 黎灿兵²

1.广东电网有限责任公司清远供电局,广东清远 511500
2.上海交通大学电力传输与功率变换控制教育部重点实验室,上海 200240
3.南京工业大学电气工程与控制科学学院,南京 211816

收稿日期:2022-01-24 修回日期:2022-03-22 出版日期:2023-01-28 发布日期:2023-01-13
通讯作者: 杨函煜 E-mail:hyang73@outlook.com.
作者简介:俞发强(1990-),工程师,主要从事配电设备运维等工作.
基金资助:
广东电网公司科技项目(GDKJXM20185779-031800KK52180097)

Optimal Sizing of Grid-Connected Wind-Solar-Biogas Integrated Energy System Considering Demand Response

YU Faqiang¹, ZHANG Mingjie¹, CHENG Yu², CHEN Dawei², YANG Hanyu³(), LI Canbing²

1. Qingyuan Power Supply Bureau, Guangdong Power Grid Co., Ltd., Qingyuan 511500, Guangdong, China
2. Key Laboratory of Power Transmission and Power Conversion Control of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
3. College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China

Received:2022-01-24 Revised:2022-03-22 Online:2023-01-28 Published:2023-01-13
Contact: YANG Hanyu E-mail:hyang73@outlook.com.

摘要/Abstract

摘要：

我国农村地区存在丰富的生物质资源,可通过发酵系统将其转化为沼气能加以利用.然而,沼气工程的产出以沼气为主,经济效益普遍较低,难以推广.提出一种由多种可再生能源构成的并网风-光-沼微能源网,利用太阳能、风能和沼气之间的互补性,为用户提供沼气和电力.根据微生物发酵动力学模型和沼气发酵的温敏特性,对沼气的类储能特性进行建模.同时考虑需求侧响应进一步增加系统灵活性,利用分时电价节省购电成本,从而将投资成本和年度运行成本降至最低.案例研究表明,该风-光-沼微能源网可稳定地向用户提供电力;并且通过参与需求响应,可使得投资成本降低3%~9%的情况下年收益增加127%~240%.

关键词: 微能源网, 沼气发电, 需求侧响应, 优化配置

Abstract:

There are abundant biomass resources in China’s rural areas, which can be converted into biogas energy through fermentation systems. However, the rewards of the investments of the pure biogas projects is poor because biogas is a cheap resource. This paper proposes a 100% renewable grid-connected wind-solar-biogas integrated energy system which utilizes the complementarity between solar energy, wind energy, and biogas to provide users with biogas and electricity. The battery-like characteristics of biogas are modeled based on the microbial fermentation kinetic model and the temperature-sensitive characteristics of biogas fermentation. In addition, the demand-side response is considered to further increase the flexibility of the system, and the time-of-use electricity price is used to save power purchase costs, thereby minimizing investment costs and annual operating costs. Case studies show that the wind-solar-biogas micro-energy network can effectively reduce the total investment cost by 3% to 9% while increasing the benefit by 1.27 to 2.40 times.

Key words: integrated energy system, biogas generation, demand response, optimal sizing

中图分类号:

TM619

俞发强, 张名捷, 程语, 陈达伟, 杨函煜, 黎灿兵. 需求响应下的并网型风-光-沼微能源网优化配置[J]. 上海交通大学学报, 2023, 57(1): 10-16.

YU Faqiang, ZHANG Mingjie, CHENG Yu, CHEN Dawei, YANG Hanyu, LI Canbing. Optimal Sizing of Grid-Connected Wind-Solar-Biogas Integrated Energy System Considering Demand Response[J]. Journal of Shanghai Jiao Tong University, 2023, 57(1): 10-16.

图/表 9

图1

图2

图3

表1

表2

表3

表4

图4

图5

参考文献 22

[1]	王文彬, 郑蜀江, 范瑞祥, 等. “双碳”背景下微网分布式电能交易绩效评价指标与方法[J]. 上海交通大学学报, 2022, 56(3): 312-324.
	WANG Wenbin, ZHENG Shujiang, FAN Ruixiang, et al. Performance evaluation index and method of micro-grid distributed electricity trading under the background of “carbon peaking and carbon neutrality”[J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 312-324.
[2]	王伟胜. 我国新能源消纳面临的挑战与思考[J]. 电力设备管理, 2021(1): 22-23.
	WANG Weisheng. China’s challenges and considerations regarding new energy consumption[J]. Electric Power Equipment Management, 2021(1): 22-23.
[3]	罗尔呷, 张宇, 冯祎宇, 等. 我国沼气产业发展的历程、现状和未来方向研究: 基于河南漯河地区的典型案例分析[J]. 中国农业资源与区划, 2022, 43(5): 132-142.
	LUO Erga, ZHANG Yu, FENG Yiyu, et al. The research on cours, current situation and future direction of China’s biogas industry development—Based on the typical case analysis of Luohe area, Henan[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2022, 43(5): 132-142.
[4]	李景明, 李冰峰, 徐文勇. 中国沼气产业发展的政策影响分析[J]. 中国沼气, 2018, 36(5): 3-10.
	LI Jingming, LI Bingfeng, XU Wenyong. Analysis of the policy impact on China’s biogas industry development[J]. China Biogas, 2018, 36(5): 3-10.
[5]	WANG Z Q, WANG J, MA M L, et al. Distributed event-triggered fixed-time fault-tolerant secondary control of islanded AC microgrid[J]. IEEE Transactions on Power Systems, 2022, 37(5): 4078-4093. doi: 10.1109/TPWRS.2022.3142153 URL
[6]	XU D, ZHOU B, CHAN K W, et al. Distributed multienergy coordination of multimicrogrids with biogas-solar-wind renewables[J]. IEEE Transactions on Industrial Informatics, 2019, 15(6): 3254-3266. doi: 10.1109/TII.2018.2877143 URL
[7]	ZHOU B, XU D, LI C B, et al. Optimal scheduling of biogas-solar-wind renewable portfolio for multicarrier energy supplies[J]. IEEE Transactions on Power Systems, 2018, 33(6): 6229-6239. doi: 10.1109/TPWRS.2018.2833496 URL
[8]	GHAEM SIGARCHIAN S, PALETA R, MALMQUIST A, et al. Feasibility study of using a biogas engine as backup in a decentralized hybrid (PV/wind/battery) power generation system—Case study Kenya[J]. Energy, 2015, 90: 1830-1841. doi: 10.1016/j.energy.2015.07.008 URL
[9]	LI C B, YANG H Y, SHAHIDEHPOUR M, et al. Optimal planning of islanded integrated energy system with solar-biogas energy supply[J]. IEEE Transactions on Sustainable Energy, 2020, 11(4): 2437-2448. doi: 10.1109/TSTE.2019.2958562 URL
[10]	杨欢红, 史博文, 黄文焘, 等. 基于综合需求响应的微能源网日前优化调度方法[J]. 电力建设, 2021, 42(7): 11-19. doi: 10.12204/j.issn.1000-7229.2021.07.002
	YANG Huanhong, SHI Bowen, HUANG Wentao, et al. Day-ahead optimized operation of micro energy grid considering integrated demand response[J]. Electric Power Construction, 2021, 42(7): 11-19. doi: 10.12204/j.issn.1000-7229.2021.07.002
[11]	刘洪, 王亦然, 李积逊, 等. 考虑建筑热平衡与柔性舒适度的乡村微能源网电热联合调度[J]. 电力系统自动化, 2019, 43(9): 50-58.
	LIU Hong, WANG Yiran, LI Jixun, et al. Coordinated heat and power dispatch of micro-energy network of countryside considering heat balance model of building and flexible indoor comfort constraint[J]. Automation of Electric Power Systems, 2019, 43(9): 50-58.
[12]	江岳春, 曾诚玉, 郇嘉嘉, 等. 计及人体舒适度和柔性负荷的综合能源协同优化调度[J]. 电力自动化设备, 2019, 39(8): 254-260.
	JIANG Yuechun, ZENG Chengyu, HUAN Jiajia, et al. Integrated energy collaborative optimal dispatch considering human comfort and flexible load[J]. Electric Power Automation Equipment, 2019, 39(8): 254-260.
[13]	李林晏, 韩爽, 乔延辉, 等. 面向高比例新能源并网场景的风光-电动车协同调度方法[J]. 上海交通大学学报, 2022, 56(5): 554-563.
	LI Linyan, HAN Shuang, QIAO Yanhui, et al. A wind-solar-electric vehicles coordination scheduling method for high proportion new energy grid-connected scenarios[J]. Journal of Shanghai Jiao Tong University, 2022, 56(5): 554-563.
[14]	YANG H Y, LI C B, SHAHIDEHPOUR M, et al. Multistage expansion planning of integrated biogas and electric power delivery system considering the regional availability of biomass[J]. IEEE Transactions on Sustainable Energy, 2021, 12(2): 920-930. doi: 10.1109/TSTE.2020.3025831 URL
[15]	WANG Z Q, WANG J, MA M L, et al. Distributed event-triggered fixed-time fault-tolerant secondary control of islanded AC microgrid[J]. IEEE Transactions on Power Systems, 2022, 37(5): 4078-4093. doi: 10.1109/TPWRS.2022.3142153 URL
[16]	RODRÍGUEZ-GALLEGOS C D, YANG D Z, GANDHI O, et al. A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study[J]. Energy, 2018, 160: 410-429. doi: 10.1016/j.energy.2018.06.185 URL
[17]	LEE J T, CALLAWAY D S. The cost of reliability in decentralized solar power systems in sub-Saharan Africa[J]. Nature Energy, 2018, 3(11): 960-968. doi: 10.1038/s41560-018-0240-y URL
[18]	RIGO-MARIANI R, SARENI B, ROBOAM X. Integrated optimal design of a smart microgrid with storage[J]. IEEE Transactions on Smart Grid, 2017, 8(4): 1762-1770. doi: 10.1109/TSG.2015.2507131 URL
[19]	HONG Y Y, LIAN R C. Optimal sizing of hybrid wind/PV/diesel generation in a stand-alone power system using Markov-based genetic algorithm[J]. IEEE Transactions on Power Delivery, 2012, 27(2): 640-647. doi: 10.1109/TPWRD.2011.2177102 URL
[20]	XU L, RUAN X B, MAO C X, et al. An improved optimal sizing method for wind-solar-battery hybrid power system[J]. IEEE Transactions on Sustainable Energy, 2013, 4(3): 774-785. doi: 10.1109/TSTE.2012.2228509 URL
[21]	SARKAR T, BHATTACHARJEE A, SAMANTA H, et al. Optimal design and implementation of solar PV-wind-biogas-VRFB storage integrated smart hybrid microgrid for ensuring zero loss of power supply probability[J]. Energy Conversion and Management, 2019, 191: 102-118. doi: 10.1016/j.enconman.2019.04.025 URL
[22]	RAHMAN M M, HASAN M M, PAATERO J V, et al. Hybrid application of biogas and solar resources to fulfill household energy needs: A potentially viable option in rural areas of developing countries[J]. Renewable Energy, 2014, 68: 35-45. doi: 10.1016/j.renene.2014.01.030 URL

电价区间	时间段	电价
电价区间	时间段	购电	售电
低谷	0—8时	0.3	0.1
	9—11时	0.3	0.1
正常	14—16时	0.5	0.3
	22—23时	0.5	0.3
峰值	12—13时	0.8	0.5
	17—21时	0.8	0.5

发酵池/m³	光伏/ kW	储气罐/m³	风电/ kW	年收益/元	总成本/元
650	249.8	808.2	629.2	11.6×10⁴	330.3×10⁴
700	208.8	845.2	591.9	17.1×10⁴	309.9×10⁴
750	166.2	930.7	562.8	24.6×10⁴	291.4×10⁴
800	124.2	1090.0	512.9	28.5×10⁴	268.8×10⁴
850	82.0	1276.9	480.2	34.3×10⁴	250.6×10⁴

发酵池/m³	光伏/ kW	储气罐/m³	风电/kW	年收益/元	总成本元
650	253.9	816.2	659.7	5.1×10⁴	339.6×10⁴
700	236.1	859.1	611.2	6.7×10⁴	325.8×10⁴
750	198.2	949.3	592.8	7.6×10⁴	311.9×10⁴
800	164.8	1180.2	552.4	8.9×10⁴	295.8×10⁴
850	123.1	1350.9	513.3	10.1×10⁴	276.1×10⁴

需求响应下的并网型风-光-沼微能源网优化配置

Optimal Sizing of Grid-Connected Wind-Solar-Biogas Integrated Energy System Considering Demand Response

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 22

相关文章 6

编辑推荐

Metrics

本文评价

[1]	夏芹芹, 罗永捷, 王荣茂, 邹尧, 罗桓桓, 李金灿, 周念成, 王强钢. 考虑新能源爬坡的风光火耦合系统源荷匹配性分析及容量优化配置[J]. 上海交通大学学报, 2024, 58(1): 69-81.
[2]	米阳, 李海鹏, 陈博洋, 彭建伟, 魏炜, 姚艳. 基于模糊场景聚类的微电网两阶段优化配置[J]. 上海交通大学学报, 2023, 57(9): 1137-1145.
[3]	刘子旭, 米阳, 卢长坤, 符杨, 苏向敬. 计及需求响应和风力发电消纳的电-热系统低碳优化调度[J]. 上海交通大学学报, 2023, 57(7): 835-844.
[4]	黄远明, 张玉欣, 夏赞阳, 王浩浩, 吴明兴, 王宁, 陈青, 朱涛, 陈新宇. 考虑需求响应资源和储能容量价值的新型电力系统电源规划方法[J]. 上海交通大学学报, 2023, 57(4): 432-441.
[5]	杨博, 王俊婷, 俞磊, 曹璞璘, 束洪春, 余涛. 基于孔雀优化算法的配电网储能系统双层多目标优化配置[J]. 上海交通大学学报, 2022, 56(10): 1294-1307.
[6]	李烁，陈震，潘尔顺. 广义逆高斯过程的步进应力加速退化试验设计[J]. 上海交通大学学报（自然版）, 2017, 51(2): 186-.

成本	发酵池/ (元·m^-3)	光伏/ (元·kW^-1)	储气罐/ (元·m^-3)	风电/ (元·kW^-1)
投资	1000	800	100	2500
运营	200	6	20	0