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

doi:10.16183/j.cnki.jsjtu.2022.017

Abstract

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

CLC Number:

TM619

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.

Figures/Tables 9

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Tab.3

Tab.4

Fig.4

Fig.5

References 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

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

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