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One of the most famous methods for minimizing power loss is distribution network reconfiguration (DNR). Accordingly, many researchers have focused their work on finding a network's optimal configuration in planning mode. However, few address the switching sequence process during operation mode. This paper introduces an innovative approach to minimize power loss in distribution networks. It addresses the often-overlooked real-time switching sequence order (SSO) during network operation, ensuring a smooth transition to the optimal configuration within operational constraints. Simultaneously, it optimizes distribution network reconfiguration (DNR) and distributed generation location and sizing (DG-LS) to maximize load capacity. The primary goal is to reduce power losses, improve voltage profiles, and enhance network efficiency. Utilizing multi-objective decision methods based on AHP, particle swarm optimization (PSO), and firefly algorithm (FA), this study achieves efficient results for SSO, DNR, and DG-LS optimization. [ABSTRACT FROM AUTHOR]

This study presents an improved under-frequency load shedding (UFLS) scheme that can detect power deficit during the shedding process and accordingly adjust the amount of load shedding. This is achieved by continuous monitoring of the overshooting signal of the second frequency derivative of the centre of inertia. Once detected, an equivalent system inertia constant is estimated in order to quantify the new power deficit. The scheme is also equipped with an optimisation algorithm to determine the best combination of loads that is close to the amount of power deficit, which minimises frequency overshoot/ undershoot. The optimisation technique selected for this work is based on particle swarm optimisation. The performance of the proposed UFLS scheme was validated using a modified IEEE 33 bus with two mini-hydro generators and one full converter wind turbine. The system and the proposed UFLS was modelled and simulated in PSCAD/EMTDC software. The results confirmed that the proposed scheme is capable of shedding loads with minimum undershoot/overshoot, and detect and estimate a new power deficit during load shedding. The results reported by the proposed scheme proved to be significantly better than those reported by conventional and adaptive load shedding schemes. [ABSTRACT FROM AUTHOR]

In a radial distribution network integrated with distributed generation (DG), frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO) is proposed for the application of the planned load shedding and under frequency load shedding (UFLS) scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time. [ABSTRACT FROM AUTHOR]