Daha iyi güç sistemi performansı ve hesaplama verimliliği için geliştirilmiş yenilikçi algoritmalarla çoklu dağıtık enerji kaynaklarının optimal planlaması

Distributed Energy Resources (DERs) are decentralized generation units, including solar PV systems, wind turbines, and energy storage technologies,that are located close to end-users. They play a crucial role in modernizing the energy grid, promoting energy independence, and mitigating the environmental impact of electricity production. This dissertation explores the optimization of DER planning across several key areas. It proposes an integrated framework for capacity planning of grid-connected nanogrids—small solar and energy storage systems that provide kilowatt-level services to individual buildings. The framework employs a techno-enviro-economic assessment to balance cost-effectiveness and sustainability. At the grid scale, widespread random DER deployment can affect grid stability and security, potentially leading to power outages. Finding the optimal capacity and location of DERs in distribution networks with multiple units is challenging and considered an NP-hard optimization problem. This study proposes a method incorporating PSO for hybrid distributed system integration and compares simultaneous and bi-level approaches for determining system size and site selection. A novel method named PS-TVPSO is introduced, addressing traditional PSO limitations by incorporating power grid topology, resistivity, and demand characteristics into the optimization steps to avoid local optima convergence. The effectiveness of these techniques is demonstrated through their application to renewable DERs with storage, significantly improving power system performance and sustainability across several distribution networks. Simulations on IEEE 33-bus and IEEE 69-bus systems, as well as a Norwegian case, validate these findings. The outcomes highlight the significance of the proposed approaches in addressing the complexities of DER planning under realistic scenarios.