Optimal scheduling in demand-side management based grid-connected microgrid system by hybrid optimization approach considering diverse wind profiles

Demand side management (DSM) is one of the trending economic strategies which shifts the elastic demand to the off-peak hours from the peak hours so as to reduce the overall generation cost of the system. The work done in this paper can be categorized in three phases. In the first phase, various wind speed to power conversion mathematical models available in literature are analysed to find out the one with maximum level of wind penetration. For second phase, an economic DSM strategy is implemented to restructure the forecasted load demand model for various participation levels. In the final phase the cost-effective optimization of two microgrid distribution systems are percolated. As an optimization tool, novel hybrid CSAJAYA has been used to carry on the study. Different types of grid participating and pricing strategies along with valve point loading effect and wind energy uncertainty are considered to amplify the complexity and practicality of the study. The generation costs reduced from 3 to 5% when the forecasted demand was reformed with 20% DSM participation for both the test systems. A detailed comparison with the results from various optimization tools studied confirms the effectiveness of the proposed hybrid approach. The hybrid optimization tool presented in this paper performs better in terms of central tendencies, nonparametric statistical analysis, and algorithm execution time.& COPY; 2023 ISA. Published by Elsevier Ltd. All rights reserved.

Automated summary

Demand side management is an economic strategy that shifts elastic demand from peak hours to off-peak hours to reduce overall generation costs. This paper categorizes its work into three phases, including analyzing wind speed to power conversion models, implementing an economic DSM strategy, and optimizing two microgrid distribution systems. The proposed hybrid optimization tool outperforms other methods in terms of central tendencies, statistical analysis, and algorithm execution time. Rating: 8/10.