article · IEEE Access
Cogeneration systems economic dispatch seeks optimal operating schedules for combined heat and power units to reduce total fuel costs while respecting technical and operational limits. A heap-based optimisation algorithm, inspired by corporate organisational hierarchies, is applied to address this scheduling problem. The method models interactions between subordinates, immediate managers, colleagues, and individual self-contributions, supplemented by adaptive penalty functions that penalise infeasible solutions based on their distance from feasibility. The approach accounts for transmission losses and valve-point effects across test networks comprising 4, 24, 84, and 96 generating units. When evaluated against other metaheuristic techniques, including supply demand optimisation, jellyfish search, marine predators algorithms, and manta ray foraging, the method achieves lower total fuel costs. The results demonstrate the efficiency, feasibility, and capability of the heap-based approach, showing particular strength when deployed on large-scale generation networks.
Thermal and electrical energy generation accounts for substantial fuel consumption and operating expenses. Developing advanced computational techniques that coordinate combined heat and power plants more effectively can help network operators reduce overall fuel expenditure. By improving operational schedules in large-scale generation facilities, computational dispatch methods offer practical ways to manage complex constraints while maintaining system efficiency.
This work applies to computational dispatch and scheduling software for utilities and operators of combined heat and power plants. By finding lower-cost operating points for large-scale systems with up to 96 units, it could assist generation planners in reducing fuel expenditure. Based on the abstract, the work is simulation-based algorithm testing on benchmark case studies, indicating an early-stage research readiness level that requires integration and testing with real-world energy management systems before commercial deployment.
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Cogeneration systems economic dispatch (CSED) provides an optimal scheduling of heat/ power generating units. The CSED aims to minimize the whole fuel cost (WFC) of the cogeneration units taking into consideration their technical and operational limits. Then, the current paper examines the first implementation of dominant bio-inspired metaheuristic called heap-based optimization algorithm (HBOA). The HBOA is powered by an adaptive penalty functions for getting the optimal operating points. The HBOA is inspired from the organization hierarchy, where the mechanism consists of the interaction among the subordinates and their immediate boss, the interaction among the colleagues, and the employee's self-contribution. Based on the infeasible solutions' remoteness from the nearest feasible point, HBOA penalizes them with various degrees. Four case studies of the CSED are implemented and analyzed, which comprise of 4, 24, 84 and 96 generating units. The HBOA is proposed to solve CSED problem with consideration of transmission losses and the valve point impacts. An investigation with the recent optimization algorithms, which are supply demand optimization (SDO), jellyfish search optimization algorithm (JFSOA), and marine predators' optimization algorithm (MPOA), the improved MPOA (IMPOA) and manta ray foraging (MRF), is developed and elaborated. From the obtained results, it is clearly observed that the optimal solutions gained, in terms of WFC, reveal the feasibility, capability, and efficiency of HBOA compared with other optimizers especially for large-scale systems. case.
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DOI: 10.1109/access.2021.3087449
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