Power systems must be prepared to match the current growing demand for electrical energy. In this paper, the transmission network plays an important role, delivering the electric power generated in conventional power plants to load centers. For the last 45 years, the transmission network expansion planning (TNEP) problem has been widely studied; nowadays, TNEP, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a literary framework for TNEP specialists. Hence, a categorization of proposed models, case studies, innovations, and solution methods of the most relevant works regarding TNEP is provided. In order to establish a complete background, not only traditional approaches, but also those involving maintenance, uncertainties in generation and demand, reliability, electricity markets, energy storage, and risk management in TNEP are highlighted. This framework can help planners to improve previous formulations and methods and can propose more efficient models to better exploit existing infrastructure and reduce costs of investment.

The distribution system reconfiguration (DSR) is a complex large-scale optimization problem, which is usually formulated with one or more objective functions and should satisfy multiple sets of linear and non-linear constraints. As the exploration of feasible solutions in large and nonconvex search space of DSR is typically hard, it is important to develop efficient algorithms and methods for finding optimal solutions for DSR problem in reasonably short computational times. In traditional DSR, the configuration of distribution network can be changed by opening and closing sectional and tie switches, where active power losses are minimized, while radial network configuration and supply to all connected loads are both preserved. Accordingly, this paper provides a comprehensive review of a number of existing metaheuristic reconfiguration methods and introduces a novel efficient genetic algorithm (efficient GA) for DSR with loss minimization. In order to demonstrate benefits and effectiveness of the proposed efficient GA for DSR, the paper also provides a detailed comparison of results with an improved genetic algorithm (improved GA) for several test systems and real distribution networks. The obtained simulation results clearly show higher accuracy and improved convergence performance of the proposed efficient GA method, compared to the improved GA and other considered reconfiguration methods.

Distribution systems play an important role, delivering the electric power of generation system to individual consumers. Distribution system reconfiguration (DSR) is a large-scale combinatorial optimization problem. For the last 45 years, the DSR problem has been widely studied; nowadays, DSR, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a literary framework for DSR specialists. A categorization of solution methods, case studies, and novelties of the most relevant works regarding DSR are provided. In order to establish a complete background, not only traditional approaches, but also those involving uncertainty, reliability, electricity market, power quality, distributed generation, capacitor placement, and switching time in DSR are highlighted. This framework can help researches to improve previous formulations and methods and can propose more efficient models to better exploit the existing infrastructure.

In modern power systems, distributed generation (DG) plays an important role in energy losses reduction, but DG penetration in such networks is restricted by technical and investment limitations. Therefore, distribution network reconfiguration (DNR) and DG operation reduce power losses more efficiently than when only DG is utilized. Also, network reconfiguration mitigates improper DG placement in such systems which are subjected to high penetration of variable loads and DG. On the other hand, electrical energy demand is estimated by load forecasting methods and therefore is a time-variant and uncertain parameter. Moreover, DG power generation is uncertain and depends on variable load power. Consequently, models presented for the reconfiguration problem should be adequately robust against load and generation uncertainties. Thus, the present paper proposes an effective robust model for reconfiguring distribution networks with load and generation uncertainties. The proposed model is sufficiently simple for implementation and is accurate enough to find the optimal solutions in acceptable computational times. The main features of the proposed model are its high robustness against uncertain parameters, in which proposed configurations are not changed easily by small variations in DG power and load amounts, and its effectiveness, which means that uncertain parameters may change the obtained solutions.

Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration.