article · IEEE Access
Planning the integration of renewable energy distributed generation units, such as solar photovoltaic systems and wind turbines, into active distribution networks poses operational challenges due to fluctuating power outputs. A novel optimisation methodology combines an improved Harris Hawks Optimiser with Particle Swarm Optimisation to solve the allocation and sizing problem for these resources. The approach accounts for the stochastic behaviour of wind and solar outputs using probability distribution functions. Formulated as a multi-objective non-linear constrained problem, the technique targets power loss reduction, voltage improvement, system stability, and annual economic savings while meeting operational network limits. The methodology was validated using standard IEEE 33-bus and 69-bus networks, alongside a practical 94-bus Portuguese distribution network. Simulation results demonstrated that the hybrid approach provides superior performance and maximizes techno-economic benefits across all scenarios compared to existing methods.
Integrating intermittent renewable sources into electrical distribution systems can destabilise the grid and increase operational costs if not managed carefully. This computational approach provides network operators with a structured way to site and size renewable generation. By managing resource uncertainty, it helps utilities maintain grid voltage and stability while minimising energy losses and capturing long-term economic savings.
This methodology could serve as an algorithmic core for grid planning software used by distribution network operators, renewable developers, and engineering consultancies. The tool addresses the optimal placement and sizing of distributed assets under uncertainty. Having been validated on simulated benchmark networks and a real-world Portuguese 94-bus system model, the research represents applied and tested algorithmic development, remaining at a pre-commercial simulation stage prior to integration into professional engineering suites.
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Optimal planning of renewable energy-based DG units (RE-DGs) in active distribution systems (ADSs) has many positive technical and economical implications and aim to increase the overall system performance. The optimal allocation and sizing of RE-DGs, particularly photovoltaic (PV) and wind turbine (WT), is still a challenging task due to the stochastic behavior of renewable resources. This paper proposed a novel methodology to solve the problem of RES-DGs planning optimization based on improved Harris Hawks Optimizer (HHO) using Particle Swarm Optimization (PSO). The uncertainties associated with the intermittent behaviour of PV and WT output powers are considered using appropriate probability distribution functions. The optimization problem is formulated as a non-linear constrained optimization problem with multiple objectives, where power loss reduction, voltage improvement, system stability, and yearly economic saving have been taken as the optimization objectives taken into account various operational constraints. The proposed methodology, namely HHO-PSO, has validated on three test systems; standard IEEE 33 bus and 69 bus systems and 94 bus practical distribution system located in Portuguese. The obtained results reveal that the HHO-PSO provide better solutions and maximizes the techno-economic benefits of the distribution systems for all considered cases and scenarios. Furthermore, simulation results are evaluated by comparing to those well-known approaches reported in the recent literature.
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DOI: 10.1109/access.2019.2947308
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