Optimal Scheduling of Intelligent Building with Photovoltaic Energy Storage System Using Competitive Mechanism Integrated Multi-objective Equilibrium Optimizer Algorithm

In recent years, distributed energy has been gradually applied in residential electricity consumption, and smart devices have been rapidly developed among residential households. This paper establishes a model of optimal scheduling system for building load, taking into account the needs of grid side...

Full description

Saved in:
Bibliographic Details
Published in:Arabian journal for science and engineering (2011) 2022-11, Vol.47 (11), p.14641-14655
Main Authors: Yi, Lingzhi, Li, Guanghua, Chen, Kefu, Liu, Jiankang, Fan, Lǜ, Gao, Xieyi
Format: Article
Language:English
Subjects:
Algorithms
Competition
Distributed generation
Electricity consumption
Electronic devices
Energy storage
Engineering
Equilibrium
Evolutionary computation
Households
Humanities and Social Sciences
multidisciplinary
Multiple objective analysis
Optimization
Photovoltaic cells
Research Article-Electrical Engineering
Residential energy
Scheduling
Science
Smart buildings
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In recent years, distributed energy has been gradually applied in residential electricity consumption, and smart devices have been rapidly developed among residential households. This paper establishes a model of optimal scheduling system for building load, taking into account the needs of grid side and customer side, and takes the total cost of electricity consumption and total deviation of electricity consumption of building residents as the optimization objectives. Then, a multi-objective equilibrium optimizer algorithm integrated competition mechanism (CMOEO) is proposed to solve the multi-objective optimization scheduling problem of building loads with multi-decision variables. The algorithm is improved from the equilibrium optimizer algorithm by introducing the competition mechanism, replacing the original exploration and exploitation constant coefficients with dynamic factors and integrating differential evolution. Through the comparison experiments of different algorithms and the different capacity of photovoltaic energy storage system (PESS), the results show that the CMOEO has fast convergence speed, strong merit-seeking ability and better population diversity. In addition, the configuration of PESS is conducive to reducing the cost of electricity for building residents and playing the role of peak-shaving and valley-filling.
ISSN:2193-567X
1319-8025
2191-4281
DOI:10.1007/s13369-022-06831-4