Abstract
Abstract Demand Side Management (DSM) is one of the ways to create interaction between the MicroGrids (MGs) and increase consumer participation in management schemes. Different algorithms and strategies have been used to execute consumption management programs which often cover a limited number of loads in several specific types. In this paper, first, the load shift method, as an optimization problem to reduce system demand peak and subscriber’s bills for various loads in smart MGs, is solved by Hybrid Particle Swarm Optimization algorithm with Sinusoidal and Cosine Acceleration Coefficient (H-PSO-SCAC). Then the study is aimed at measuring the effect of the proposed program on the generation and presence of MGs in the market for improving the level of social welfare. The results are performed on a Smart Grid (SG) consisting of three residential, commercial and industrial MGs which include different types of controllable loads. The results show that the highest percentages of peak load reduction after the implementation of the DSM program by (H-PSO-SCAC) algorithm for the three MGs are 23%, 19% and 19%, respectively. Also, the highest percentages of reduction in subscriber’s bill for the three MGs are 16.8%, 19.2% and 20.5%, respectively. The proposed algorithm has performed much better in reducing bills and peak loads than most other methods such as Logarithmic Function (LF), Multi Agent (MA), Evolutionary Algorithm (EA), and Symbiotic Organisms Search (SOS). The findings show that the proposed program can reduce peak load, reduce subscriber’s bills, save production costs, help balance the supply and demand, and improve the level of social welfare from the perspective of the distribution system operator.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.