Distribution Systems Reconfiguration Considering Dependency of Loads on Grid Voltage and Temperature

Network reconfiguration is an effective technique to reduce lost power in distribution systems, where losses are significantly greater than the ones in transmission. The distribution power loss produces a costly operation and a degraded voltage profile over the electric power systems. In traditional reconfiguration, the topology of the distribution network is efficiently modified to achieve minimum power losses based on the electric energy requested by end-users. Various types of energy consumers are connected to load points of actual distribution networks that cause different power losses compared to mono-type loads. However, the majority of models propose distribution reconfiguration problems disregarding consumer diversity. The few studies that have included load type in their proposed reconfiguration strategies present non-linear formulations for the problem and do not consider the impact of ambient temperature on network topology. However, non-linear models can be solved by metaheuristic algorithms without guaranteed optimal solutions or can be computed by non-linear solvers in classic optimization tools but require intensive and time-consuming computations that restrict their real-world applications. Moreover, environmental temperature affects electricity consumption, and therefore, the selection of appropriate switching combinations. Therefore, the current paper introduces an efficient model for the reconfiguration of distribution systems considering various load types with their dependencies on environment temperature rise that can be easily implemented by linear solvers in commercial optimization software. The results indicate that the proposed model is precise enough to find accurate solutions for desired reconfiguration problems and is adequately fast for online reconfigurations, showing significant effect of environment temperature on the configuration of distribution systems through load and power losses changes.