TRADING MODEL AND PRODUCTION ANALYSIS OF RESIDENTIAL PHOTOVOLTAIC GRID-CONNECTED TWO-STAGE ENERGY

Yan Xiuying; Liu Pan; Chang Juan; Yan Xiulian

doi:10.19912/j.0254-0096.tynxb.2023-0901

PDF(2454 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (10) : 309-316. DOI: 10.19912/j.0254-0096.tynxb.2023-0901

TRADING MODEL AND PRODUCTION ANALYSIS OF RESIDENTIAL PHOTOVOLTAIC GRID-CONNECTED TWO-STAGE ENERGY

Yan Xiuying¹, Liu Pan¹, Chang Juan², Yan Xiulian³

Author information +

History +

Abstract

Aiming at the problem of how to realize the friendly interaction between the residents side and the grid side,this paper establishes a two-stage optimization model for grid connection. In the first stage, the optimization goal is to minimize the cost of electricity for residential users. In the second stage, the optimization goal is to minimize the average return period under the addition of photovoltaic-energy storage grid-connected operation. Firstly, the multi-user scheduling model is simplified by means of probabilistic statistics, which is equivalent to the sum of four types of characteristic user scheduling and solved by PSO algorithm. Secondly, a residential home energy management system and energy trading mode are proposed, and the trading mode is put into production analysis. The results of the example analysis show that the two-stage optimization model dispatching system can effectively reduce the peak and adjust the valley, and save the electricity cost.

Key words

energy management / photovoltaic / energy storage / energy trading / production analysis

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Yan Xiuying, Liu Pan, Chang Juan, Yan Xiulian. TRADING MODEL AND PRODUCTION ANALYSIS OF RESIDENTIAL PHOTOVOLTAIC GRID-CONNECTED TWO-STAGE ENERGY[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 309-316 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0901

References

[1] ZHU J W, LIN Y S, LEI W D, et al.Optimal household appliances scheduling of multiple smart homes using an improved cooperative algorithm[J]. Energy, 2019, 171: 944-955.
[2] ZHU J W, LAURI F, KOUKAM A, et al.A hybrid intelligent control based cyber-physical system for thermal comfort in smart homes[J]. International journal of ad hoc and ubiquitous computing, 2019, 30(4): 199-214.
[3] 宋子晔, 秦陶, 牛擎宇, 等. 基于智能家电管理的家庭能源管理系统综述[J]. 建筑节能(中英文), 2021, 49(9): 171-177.
SONG Z Y, QIN T, NIU Q Y, et al.A review of home energy management system based on smart appliance management[J]. Building energy efficiency, 2021, 49(9): 171-177.
[4] 金森钧. 基于分布式发电和储能的家庭能量管理系统设计与优化调度算法研究[D]. 杭州: 浙江大学, 2017.
JIN S J.Research on design and optimal scheduling algorithm of home energy management system based on distributed generation and energy storage[D]. Hangzhou: Zhejiang University, 2017.
[5] 于军琪, 侯雪妍, 赵安军, 等. 基于改进天牛须算法的家庭能量管理系统多目标优化调度[J]. 电力系统及其自动化学报, 2022, 34(5): 79-86.
YU J Q, HOU X Y, ZHAO A J, et al.Multi-objective optimal scheduling of household energy management system based on improved beetle antennae search algorithm[J]. Proceedings of the CSU-EPSA, 2022, 34(5): 79-86.
[6] 傅质馨, 李紫嫣, 朱俊澎, 等. 面向多用户的多时间尺度电力套餐与家庭能量优化策略[J]. 电力系统保护与控制, 2022, 50(11): 21-31.
FU Z X, LI Z Y, ZHU J P, et al.Multi-user multi-timescale power packages and home energy optimization strategies[J]. Power system protection and control, 2022, 50(11): 21-31.
[7] 刘永春, 蔡华, 田中利, 等. 基于双层博弈的居民家电负荷聚合测试方法[J]. 电力需求侧管理, 2022, 24(5): 78-83.
LIU Y C, CAI H, TIAN Z L, et al.Load aggregation test for household appliances based on double-layer game[J]. Power demand side management, 2022, 24(5): 78-83.
[8] 何义. 智能楼宇可控负荷的用电特性及其需求响应潜力研究[D]. 湘潭: 湘潭大学, 2020.
HE Y.Research on power consumption characteristics and demand response potential of controllable load in intelligent buildings[D]. Xiangtan: Xiangtan University, 2020.
[9] 江泽昌, 刘天羽, 江秀臣, 等. 智能电网下多时间尺度家庭能量管理优化策略[J]. 太阳能学报, 2021, 42(1): 460-469.
JIANG Z C, LIU T Y, JIANG X C, et al.Multi-time scale home energy management optimization stratery in smart grid[J]. Acta energiae solaris sinica, 2021, 42(1): 460-469.
[10] 潘华, 梁作放, 肖雨涵, 等. 多场景下区域综合能源系统的优化运行[J]. 太阳能学报, 2021, 42(1): 484-492.
PAN H, LIANG Z F, XIAO Y H, et al.Optimal operation of regional integrated energy system under multiple scenes[J]. Acta energiae solaris sinica, 2021, 42(1): 484-492.
[11] 李菁, 王志新, 严胜, 等. 计及舒适度的家庭能量管理系统优化控制策略[J]. 太阳能学报, 2020, 41(10): 51-58.
LI J, WANG Z X, YAN S, et al.Optimal operation of home energy management system considering user comfort preference[J]. Acta energiae solaris sinica, 2020, 41(10): 51-58.
[12] HABIB A H, RATNAM E L, DISFANI V R, et al.Optimization-based residential load scheduling to improve reliability in the distribution grid[C]//2016 IEEE 55th Conference on Decision and Control (CDC). Las Vegas, NV, USA, 2016: 2419-2424.
[13] 蔡钦钦, 杨晓华, 朱永强. 楼宇能量管理系统的光伏消纳与储能调度研究[J]. 电力建设, 2020, 41(1): 23-31.
CAI Q Q, YANG X H, ZHU Y Q.Research on photovoltaic accommodation and energy storage scheduling of building energy management system[J]. Electric power construction, 2020, 41(1): 23-31.
[14] SHAKERI M, SHAYESTEGAN M, ABUNIMA H, et al.An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid[J]. Energy and buildings, 2017, 138: 154-164.
[15] 董涛, 雍静, 赵瑾, 等. 含光、储、电动汽车居民小区电力负荷综合管理系统[J]. 重庆大学学报, 2021, 44(8): 45-58.
DONG T, YONG J, ZHAO J, et al.Load management approach for residential power system incorporating photovoltaics, electric storage and electric-vehicle charging[J]. Journal of Chongqing University, 2021, 44(8): 45-58.