Sensitivity Analysis Based Multi-Objective Economic Emission Dispatch in Microgrid

Document Type : Research paper

Authors

1 Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India

2 Department of Electrical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal

3 Deputy Director, National Power Training Institute, Faridabad, Haryana, India

Abstract

The microgrid (μG) is an integration of distributed generation and local loads with energy storage system. Cost minimization is one of the main objectives in modern power systems.Economic dispatch(ED) is a fundamental problem related to μG and the conventional grid. Economic dispatch(ED) provides the optimal output of generators in order to reduce the total operating cost. Emission dispatch (EMD) is one of the other major problems associated with CG. The emission dispatch (EMD) solution provides the optimal generator operation to reduce harmful pollutants for a specific load demand. Multi-objective economic emission dispatch (MEED) provides a compromise between ED and EMD. In this paper, two test systems have been proposed. Test system one consists of Six CG. Static ED, EMD, and MOEED analysis has been provided for test system one. Test system two consists of four CG, One wind turbine generator (WTG), and one photovoltaic module (PVM).This paper intends to provide sensitivity analysis and uncertainty regarding the curtailment cost of RES. CPLEX solver in GAMS has been proposed to optimize the three fundamental problems. Comparative study and sensitivity analysis show optimal results, and the GAMS solver provides a more comprehensive framework. Reduction in cost due to uncertainty in ED is 9.58% as compared to 9.7% for test system two. The cost has been reduced in MEED by 9.33% as compared to 9.46%. MEED comparison shows the increment in cost of 2.66 %, but the emission is reduced by 18.98 % for test system two.

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Journal of Operation and Automation in Power Engineering

Articles in Press, Corrected Proof
Available Online from 16 September 2023

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  • Receive Date: 08 March 2023
  • Revise Date: 16 May 2023
  • Accept Date: 27 June 2023

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