OPTIMIZED DESIGN METHOD OF PV-BATTERY ENERGY SYSTEM FOR RESIDENTIAL BUILDINGS IN CHINA SOLAR-RICH AREA

Xu Xinyin; Feng Hengli; Yang Liu; Liu Yan

doi:10.19912/j.0254-0096.tynxb.2023-1546

PDF(2267 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (7) : 101-110. DOI: 10.19912/j.0254-0096.tynxb.2023-1546

OPTIMIZED DESIGN METHOD OF PV-BATTERY ENERGY SYSTEM FOR RESIDENTIAL BUILDINGS IN CHINA SOLAR-RICH AREA

Xu Xinyin^1,2, Feng Hengli¹, Yang Liu^1,3, Liu Yan^1,3

Author information +

History +

Abstract

This paper constructs models for the various components of the system, with the annual total cost and the building self-sufficiency as the objective functions and PV installation parameters and capacity, and battery capacity as the decision variables. By balancing energy flow and equipment efficiency, we obtained the design parameters of the PV-battery system by utilizing non-dominated sorting genetic algorithm（NSGA-Ⅱ）. The enhanced TOPSIS method was employed to determine the optimal system capacity across varying scenarios. Using residential buildings in Lhasa as a case study, we explored and validated the methodology's practicality. Our findings show that this approach effectively determines the PV-battery system's installation and capacity parameters, meeting dual objectives of building autonomy and cost-effectiveness. Meanwhile, the decision of whether excess electricity is fed back to the grid significantly influences the design of the energy system.

Key words

solar energy / battery storage / optimization / NSGA-Ⅱ algorithm / TOPSIS

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Xu Xinyin, Feng Hengli, Yang Liu, Liu Yan. OPTIMIZED DESIGN METHOD OF PV-BATTERY ENERGY SYSTEM FOR RESIDENTIAL BUILDINGS IN CHINA SOLAR-RICH AREA[J]. Acta Energiae Solaris Sinica. 2024, 45(7): 101-110 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1546

References

[1] 刘加平, 谢静超. 广义建筑围护结构热工设计原理与方法[J]. 建筑科学, 2022, 38(8): 1-8.
LIU J P, XIE J C.Generalized principle and method of thermal design for building envelopes[J]. Building science, 2022, 38(8): 1-8.
[2] 中国气象局风能太阳能中心. 2022年中国风能太阳能资源年景公报[R]. 北京: 中国气象局风能太阳能中心, 2023.
CMA Wind and Solar Energy Centre. China wind and solar energy resources bulletin[R]. Beijing CMA Wind and Solar Energy Center, 2023.
[3] SONG Z, CAO S L, YANG H X.Assessment of solar radiation resource and photovoltaic power potential across China based on optimized interpretable machine learning model and GIS-based approaches[J]. Applied energy, 2023, 339: 121005.
[4] 刘艳峰, 李荟婷, 王登甲, 等. 太阳能集热系统过热影响因素分析[J]. 太阳能学报, 2021, 42(3): 463-468.
LIU Y F, LI H T, WANG D J, et al.Factor analysis of overheating in solar collector system[J]. Acta energiae solaris sinica, 2021, 42(3): 463-468.
[5] 王登甲, 刘艳峰. 西藏高原太阳能供暖“高原病” 问题探讨[J]. 暖通空调, 2021, 51(8): 7-11.
WANG D J, LIU Y F.“Altitude sickness” problem of solar heating in Tibetan plateau[J]. Heating ventilating & air conditioning, 2021, 51(8): 7-11.
[6] ZIAR H, MANGANIELLO P, ISABELLA O, et al.Photovoltatronics: intelligent PV-based devices for energy and information applications[J]. Energy & environmental science, 2021, 14(1): 106-126.
[7] CHAIBI Y, ALLOUHI A, SALHI M, et al.Annual performance analysis of different maximum power point tracking techniques used in photovoltaic systems[J]. Protection and control of modern power systems, 2019, 4(1): 15.
[8] CHAIANONG A, BANGVIWAT A, MENKE C, et al.Customer economics of residential PV battery systems in Thailand[J]. Renewable energy, 2020, 146: 297-308.
[9] RAMIREZ CAMARGO L, NITSCH F, GRUBER K, et al.Electricity self-sufficiency of single-family houses in Germany and the Czech Republic[J]. Applied energy, 2018, 228: 902-915.
[10] 贾禾, 彭晋卿, 李念平, 等. 动态电价下分布式光伏-储能系统优化与经济性分析[J]. 太阳能学报, 2021, 42(5): 187-193.
JIA H, PENG J Q, LI N P, et al.Optimization and economic analysis of distributed photovoltaic-energy storage system under dynamic electricity price[J]. Acta energiae solaris sinica, 2021, 42(5): 187-193.
[11] GB 50797—2012, 光伏发电站设计规范[S].
GB 50797—2012, Code for design of photovoltaic power station:[S].
[12] CHEN Y W, QUAN M C, WANG D J, et al.Energy, exergy, and economic analysis of a solar photovoltaic and photothermal hybrid energy supply system for residential buildings[J]. Building and environment, 2023, 243: 110654.
[13] ALAM M M, RAHMAN M H, AHMED M F, et al.Deep learning based optimal energy management for photovoltaic and battery energy storage integrated home micro-grid system[J]. Scientific reports, 2022, 12: 15133.
[14] 申泽渊, 赵海波, 李伟康, 等. 面向偏远地区低碳发展的风-光-沼-储综合能源微网多目标规划方法[J]. 太阳能学报, 2023, 44(7): 71-79.
SHEN Z Y, ZHAO H B, LI W K, et al.Multi-objective optimization method for low-carbon development of wind-solar-biogas-storage integrated energy microgrids in remote regions[J]. Acta energiae solaris sinica, 2023, 44(7): 71-79.
[15] 赵铁军, 孟菁, 王珺, 等. 互动模式下光伏与电采暖蓄热容量优化配置策略[J]. 电力系统及其自动化学报, 2021, 33(5): 9-15.
ZHAO T J, MENG J, WANG J, et al.Optimal allocation strategy for photovoltaic and electric heating thermal storage capacities in interactive mode[J]. Proceedings of the CSU-EPSA, 2021, 33(5): 9-15.
[16] NIVEDITHA N, RAJAN SINGARAVEL M M. Optimal sizing of hybrid PV-wind-battery storage system for net zero energy buildings to reduce grid burden[J]. Applied energy, 2022, 324: 119713.
[17] 熊宇峰, 司杨, 郑天文, 等. 考虑热电综合利用的光伏储氢独立供能系统容量优化配置[J]. 中国电力, 2020, 53(10): 66-73.
XIONG Y F, SI Y, ZHENG T W, et al.Optimal capacity configuration of solar-hydrogen independent power-supply system considering electricity-heat comprehensive utilization[J]. Electric power, 2020, 53(10): 66-73.
[18] LAINE H S, SALPAKARI J, LOONEY E E, et al.Meeting global cooling demand with photovoltaics during the 21st century[J]. Energy & environmental science, 2019, 12(9): 2706-2716.
[19] ABDELAAL A K, EL-FERGANY A.Estimation of optimal tilt angles for photovoltaic panels in Egypt with experimental verifications[J]. Scientific reports, 2023, 13: 3268.
[20] DUFFIE DECEASED J A, BECKMAN W A, BLAIR N. Solar engineering of thermal processes, photovoltaics and wind[M]. New Jersey: Wiley, 2020.
[21] 西安建筑科技大学. 建筑节能设计基础参数数据平台[EB/OL].https://buildingdata.xauat.edu.cn.
Xi'an University of Architecture and Technology. Fundamental data sharing platform for building energy efficiency design[EB/OL].https://buildingdata.xauat.edu.cn.
[22] CAMPANA P E, LI H, ZHANG J, et al.Economic optimization of photovoltaic water pumping systems for irrigation[J]. Energy conversion and management, 2015, 95: 32-41.
[23] HOU H, XUE M Y, XU Y, et al.Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load[J]. Applied energy, 2020, 262: 114489.
[24] DEB K, PRATAP A, AGARWAL S, et al.A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE transactions on evolutionary computation, 2002, 6(2): 182-197.
[25] TOBISZEWSKI M, NAMIEŚNIK J, PENA-PEREIRA F. Environmental risk-based ranking of solvents using the combination of a multimedia model and multi-criteria decision analysis[J]. Green chemistry, 2017, 19(4): 1034-1042.
[26] TZENG G H, HUANG J J.Multiple attribute decision making: methods and applications[M]. New York: Springer, 2011.
[27] 中国光伏行业协会. 中国光伏产业发展路线图[R]. 北京: 中国光伏行业协会, 2021.
China Photovoltaic Industry Association. China PV industry development roadmap[R]. Beijing: China photovoltaic industry association, 2021.
[28] IRENA. Renewable power generation costs in 2021[R]. Abu Dhabi: International Renewable Energy Agency, 2021.
[29] COELLO C C A, LECHUGA M S. MOPSO: a proposal for multiple objective particle swarm optimization[C]// Proceedings of the 2002 Congress on Evolutionary Computation. Honolulu, HI, USA, 2002: 1051-1056.
[30] SUNDARAM A, ERDOGMUS P.Particle swarm optimization with applications: solution of combined economic emission dispatch problem with valve-point effect using hybrid NSGA II-MOPSO[M]. London: IntechOpen, 2018.