Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

Design and management of a distributed hybrid energy system through smart contract and blockchain

Techno-economic analysis of the lithium-ion and lead-acid battery in microgrid systems

Multi-objective energy management in a micro-grid

Demand side management in a smart micro-grid in the presence of renewable generation and demand response

Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management

In recent years, many studies have studied economic dispatch problem in power systems. However, most of them have not considered the environmental pollution caused by fossil fuels. In this study, the use of an evolutionary search algorithm
 called multi-objective particle swarm optimization algorithm is proposed to solve the economic dispatch problem in power systems while considering environmental pollution. The proposed method is validated in terms of its accuracy and convergence speed based on comparisons with the results obtained using the classic nonlinear programming method. The proposed strategy is applied to a realistic power system under various conditions. Overall, six generating units are investigated along the corresponding constraints. The results obtained reveal that costs of operation and pollution with/without power loss are reduced significantly by the proposed approach. Obtained results show a good compromise can be established between two contradicting functions of exploitation cost and pollution by optimizing them simultaneously. Values of these function without considering their loss is 46,112.09 $/h and 682.32 kg/h, respectively. And if losses are considered, these values would be 48,381.09 $/h and 726.52 kg/h, respectively.

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Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

The optimal operation of micro-grids has attracted the attention of many developed societies considering different objectives, such as the operational cost, pollution rate, and the increasingly extensive use of renewable energy resources in this field. The aggregation of these mostly contradictory goals in an optimization problem can provide an appropriate response for the users of these systems. In this study, in order to manage energy in systems with various micro-grids that differ in quality, we aim to apply the multi-objective particle swarm optimization method to obtain the optimal distribution of energy resources in a sample micro-grid, while simultaneously satisfying economic and pollution related operational objectives.

Gholamreza Aghajani

Papers

Multi-objective energy management in a micro-grid

Demand side management in a smart micro-grid in the presence of renewable generation and demand response

Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

Multi-objective optimal operation in a micro-grid considering economic and environmental goals