article · Alexandria Engineering Journal
An improved marine predators optimisation algorithm addresses the combined heat and power economic dispatch problem. This scheduling challenge seeks to minimise the overall fuel costs of cogeneration systems while adhering to operational constraints across both heat and electricity generation units. The performance of the improved algorithm was evaluated alongside the standard algorithm using four benchmark systems of varying scales. These benchmarks comprised a small five-unit setup, a medium forty-eight-unit network, and two large configurations containing eighty-four and ninety-six units distributed between power-only, heat-only, and combined generation assets. Testing indicates that the improved approach produces efficient and feasible optimal solutions across small, medium, and large networks. Furthermore, it achieves stable convergence and reaches optimal solutions more rapidly than the conventional marine predators optimisation technique.
Generating heat and electricity simultaneously can cut energy waste, but coordinating diverse equipment to minimise fuel consumption is mathematically complex. By providing faster and more reliable schedules for generation assets across both small and large facilities, effective optimisation tools help plant operators lower overall fuel expenditure while meeting operational limits and demand requirements.
This optimisation technique could be integrated into energy management software used by utilities, industrial plant operators, and district energy providers managing combined heat and power systems. Because the research evaluates the algorithm on standard mathematical test systems of up to ninety-six units rather than live grid deployments, the method sits at an early, algorithmic stage of development that requires software integration and field validation before commercial deployment.
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This paper proposes an improved marine predators’ optimization algorithm (IMPOA) for solving the combined heat and power (CHP) economic dispatch problem. This problem provides optimal scheduling of heat and power generation supplies and pursues to minimize the overall fuel cost (OFC) supply of cogeneration units considering their operational constraints. Four test systems are considered to check the performance of both the MPOA and the proposed IMPOA. The first test system is small sized which involve 5-unit, whereas the second system is medium sized which contains 48-unit system. The third and fourth test systems are large sized systems. The third test system includes 84-unit, which are divided into 40 power-only units, 20 heat only units, and 24 CHP units. The fourth test system includes 96-unit, which are divided into 52 power-only units, 20 heat-only units, and 24 CHP units. The obtained results clearly show the capability, efficiency, and feasibility of the IMPOA with respect to other relevant optimization techniques for optimal solutions of small, medium and large-scale systems. Additionally, the convergence characteristics of the proposed IMPOA are stable and the arrival of the optimal solution is faster than the conventional MPOA.
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DOI: 10.1016/j.aej.2021.07.001
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