article · IET Generation Transmission & Distribution
Managing renewable energy resources within microgrids requires balancing operating expenses against pollutant emissions, particularly when faced with operational uncertainties. A multi-objective optimisation framework addresses this economic-emission dispatch challenge for both isolated and grid-connected microgrids. Formulated as a non-linear constrained problem, the system simultaneously minimises total generation costs and emissions. The scheduling approach is powered by an enhanced moth-flame optimisation algorithm and was evaluated across nine simulated operating conditions. These test cases simulated complex disruptions, including unexpected surges in electricity demand, shortages in battery storage capacity, and the partial shedding of solar photovoltaic units. Comparative evaluations against established benchmark algorithms demonstrated that the enhanced moth-flame approach reliably converges on global solutions. This method achieves notable financial and environmental advantages while ensuring flexible, robust scheduling across uncertain operating environments.
Microgrids must provide reliable electricity without excessive costs or high emissions. Disruptions such as sudden equipment shortfalls or unexpected demand spikes can destabilise energy delivery. Applying advanced optimisation techniques enables power systems to balance economic performance and environmental standards simultaneously, helping clean power systems remain resilient and dependable during uncertain operating conditions.
This framework could be incorporated into energy management software used by microgrid operators, utilities, and hybrid renewable system developers to manage power scheduling and grid disruptions. Because the findings are validated solely through nine simulation scenarios rather than physical hardware or live grid deployments, the technology currently sits at an early stage of applied research that requires field testing before commercial deployment.
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This study proposes a framework for economic–emission dispatch problem (EEDP) in microgrids (MGs). The problem of EEDP aims at finding the optimal scheduling of renewable energy resources (RERs) in isolated and grid‐connected MGs. The EEDP is formulated as a non‐linear constrained multi‐objective optimisation problem. It minimises the total cost and emission simultaneously. Simulation results in nine different cases are conducted to emulate the complexity of the EEDP. Also, the proposed scheduling procedure is tested under abnormal operation of MGs considering unexpected increase in power demand, shortage of battery storage and partial shedding of photovoltaic units. These cases reveal the capability of the proposed method. A multi‐objective function is employed to increase the economic benefits and minimise emission issues. In this line, the simulation results are obtained using an enhanced moth‐flame optimisation (EMFO) algorithm. The obtained results verified the effectiveness, robustness and global convergence for minimising emission and generation costs. These results are compared with several well‐known techniques in the literature. Notable economic and environmental benefits are achieved using the EMFO that lead to flexible scheduling of RERs for MG operation under uncertainty.
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DOI: 10.1049/iet-gtd.2019.0739
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