article · Mathematics
A hybrid meta-heuristic algorithm combining heap-based and jellyfish search techniques, termed HBJSA, has been created to solve the combined heat and power economic dispatch problem in electrical grids. The approach merges the explorative capabilities of the heap-based algorithm with the exploitative mechanisms of the jellyfish search algorithm to enhance overall optimisation performance. The method was evaluated on meeting heat and electricity demands while minimising total fuel costs, accounting for operational constraints such as non-convex operating zones and valve-point loading effects. Testing was performed across medium test systems of 24 and 48 units as well as large networks of 84 and 96 units. Across these benchmarks, the hybrid method delivered superior fuel cost reductions and displayed greater stability and robustness compared with its parent algorithms and alternative reported methods.
Balancing heat and power production while keeping fuel costs as low as possible is a complex challenge for energy networks. By using an improved hybrid search strategy to resolve non-linear grid constraints, power operators can reduce fuel expenditure and maintain reliable thermal and electrical supplies across systems of varying size.
This optimisation method could be incorporated into energy management software used by electrical grid operators, microgrid managers, and combined heat and power plant engineers to minimise operational fuel costs. Based on simulation testing on standard test systems ranging from 24 to 96 units, the technology represents applied and tested computational research that requires software development and real-world grid trial integration before full commercial deployment.
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This paper proposes a hybrid algorithm that combines two prominent nature-inspired meta-heuristic strategies to solve the combined heat and power (CHP) economic dispatch. In this line, an innovative hybrid heap-based and jellyfish search algorithm (HBJSA) is developed to enhance the performance of two recent algorithms: heap-based algorithm (HBA) and jellyfish search algorithm (JSA). The proposed hybrid HBJSA seeks to make use of the explorative features of HBA and the exploitative features of the JSA to overcome some of the problems found in their standard forms. The proposed hybrid HBJSA, HBA, and JSA are validated and statistically compared by attempting to solve a real-world optimization issue of the CHP economic dispatch. It aims to satisfy the power and heat demands and minimize the whole fuel cost (WFC) of the power and heat generation units. Additionally, a series of operational and electrical constraints such as non-convex feasible operating regions of CHP and valve-point effects of power-only plants, respectively, are considered in solving such a problem. The proposed hybrid HBJSA, HBA, and JSA are employed on two medium systems, which are 24-unit and 48-unit systems, and two large systems, which are 84- and 96-unit systems. The experimental results demonstrate that the proposed hybrid HBJSA outperforms the standard HBA and JSA and other reported techniques when handling the CHP economic dispatch. Otherwise, comparative analyses are carried out to demonstrate the suggested HBJSA’s strong stability and robustness in determining the lowest minimum, average, and maximum WFC values compared to the HBA and JSA.
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DOI: 10.3390/math9172053
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