article · IEEE Access
Managing modern electric power systems requires balancing operational expenses, power losses, and environmental emissions. The introduction of voltage source converter stations and multi-terminal direct current links into alternating current networks alters power flow dynamics and control requirements. An improved manta ray foraging optimisation algorithm addresses these multi-objective challenges in both conventional meshed grids and hybrid alternating and direct current configurations. The algorithm models manta ray feeding behaviours, using an external repository to store non-dominated solutions and an adaptive weighting mechanism to evaluate operational trade-offs. A decision-making method based on similarity to ideal solutions selects preferred operating set points from the resulting frontier. Validated on standard and modified thirty-bus test systems, the approach effectively minimises fuel costs, electrical losses, and emissions, demonstrating superior robustness compared to other optimisation techniques.
Modernising power grids with high-voltage direct current links and converter stations introduces operational complexity. Grid operators require sophisticated computational methods to balance conflicting demands, such as lowering electricity generation expenses, cutting carbon emissions, and minimising line losses. Robust multi-objective optimisation tools help power utilities maintain reliable, cost-effective, and environmentally sustainable system operations as network architectures evolve.
The work could be incorporated into grid analysis software used by transmission system operators and utility planners managing hybrid alternating and direct current networks. It enables automated evaluation of optimal dispatch set points across complex converter-based architectures. As the findings are based solely on simulated test networks rather than physical utility deployments, the technology represents early-stage software research that requires validation on full-scale power systems before commercial adoption.
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It is no doubt that the optimal power flow (OPF) has great importance in electric power systems. It aims at assigning the adequate operating levels in order to meet the required demands with the objective of minimizing combined economic and environmental concerns. Integration of emerged technologies of voltage source converter (VSC) stations in AC meshed power systems changes foremost their corresponding operation and control features. The VSC stations are usually connected with each other through HVDC lines and consequently a multi-terminal direct current (MDC) system is established. This paper presents an improved manta ray foraging optimizer (IMRFO) for solving the OPF in electric power systems with and without emerged technologies of VSC stations. The proposed IMRFO aims at minimizing the total fuel costs, the total environmental emissions, and the total electrical losses. The MRFO simulates the foraging behaviors of the manta rays. MRFO is improved to handle multi-objectives by incorporating an outward store for the non-dominated Pareto individuals. The form of the fitness function is adaptively varied by iteratively changing their weights. Furthermore, a technique for order preference by similarity to ideal solution (TOPSIS) is applied to extract a suitable operating point among the resulted Pareto set. Several applications of the proposed IMRFO are presented for conventional IEEE 30-bus system, as an AC meshed power system, and modified IEEE 30-bus with emerged VSC stations, as a hybrid AC/MDC meshed power system. Simulation results declare that the proposed algorithm has great effectiveness and robustness features compared to the others. Also, various well-distributed Pareto solutions are obtained based on the proposed algorithm with adequate techno-economic-environmental characteristics.
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DOI: 10.1109/access.2020.3022919
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