Combating climate change issues resulting from excessive use of fossil fuels comes with huge initial costs, thereby posing difficult challenges for the least developed countries in Sub-Saharan Africa (SSA) to invest in renewable energy alternatives, especially with rapid industrialization. However, designing renewable energy systems usually hinges on different economic and environmental criteria. This paper used the Multi-Objective Particle Swarm Optimization (MOPSO) technique to optimally size ten grid-connected hybrid blocks selected amongst Photo-Voltaic (PV) panels, onshore wind turbines, biomass combustion plant using sugarcane bagasse, Battery Energy Storage System (BESS), and Diesel Generation (DG) system as backup power, to reduce the supply deficit in Sierra Leone. Resource assessment using well-known methods was done for PV, wind, and biomass for proposed plant sites in Kabala District in Northern and Kenema District in Southern Sierra Leone. Long term analysis was done for the ten hybrid blocks projected over 20 years whilst ensuring the following objectives: minimizing the Deficiency of Power Supply Probability (DPSP), Diesel Energy Fraction (DEF), Life Cycle Costs (LCC), and carbon dioxide (CO 2 ) emissions. Capacity factors of 27.41 % and 31.6 % obtained for PV and wind, respectively, indicate that Kabala district is the most feasible location for PV and wind farm installations. The optimum results obtained are compared across selected blocks for DPSP values of 0–50% to determine the most economical and environmentally friendly alternative that policy makers in Sierra Leone and the region could apply to similar cases.

Summary The performance of a new approach for multiobjective voltage stability constrained‐optimal power flow (VSC‐OPF) formulation is compared with a conventional VSC‐OPF approach for improving the steady‐state power systems security in this paper. The compared OPF problems involve the minimization of the fuel cost and minimization of novel line stability index (NLSI) for case 1 and minimization of fuel cost and maximization of line static stability margin (CBI) for the proposed case 2. Clerc's constricted PSO algorithm modified with the nondominated sorting algorithm is used for obtaining the best solution point for each of the decision variables. Network security constraints and bus voltage limits are considered along with the constraint on permissible line stability margin limit adopting the quadratic penalty model for constraints violations. The approach is tested on a load‐modified IEEE 30‐bus and actual Nigerian 28‐bus systems. From the results obtained, the proposed OPF formulation performed better for simultaneous consideration of voltage stability improvement and line loss reduction.

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