Optimal allocation of remote controlled switches in radial distribution systems

Abstract

There is an increasing interest in the analysis of power distribution systems, including demands to improve the distribution networks reliability. Regulatory agencies define reliability indices to quantify and evaluate the electric quality. In order to improve system reliability and provide a good quality service, this work proposes to install a minimum amount of switch devices at appropriate locations in the distribution network.A methodology is presented to effectively evaluate, even for large real networks the impact on reliability following contigencies.Firstly, are propose a constructive heuristic that allocates sectionalizers and tie switches, automatic and non-automatic, in a radial distribution system. This procedure aims to minimize the unsupplied energy caused in the network by determining a proper number, location and type of switches. A genetic algorithm is designed to further improve the switches location suggested by the constructive heuristic.The good performance of the proposed approach is confirmed by some case studies with large real energy distribution network.

Optimal deployment of remote‐controlled switches in distribution networks considering laterals

“…Besides the mentioned literature, there are a few papers that introduced heuristic algorithms in order for determining the location of RCSs in both main feeder and laterals. Among these papers, greedy algorithms [18], analytic hierarchical process methods [19], genetic algorithms [20], and memetic algorithms [21] were used to allocate RCSs in the entire network. Although Xu et al [18], Bernadron et al [19], and de Assis et al [20,21] considered the entire network, but have drawbacks such as solution speed, dependency on parameter tuning, different solutions in different simulations, and no proof on the optimality of the solution.…”

“…CI RCS + IC RCS ≤ Budget (20) where (19) limits the number of RCSs in the network and (20) restricts the investment and installation costs of RCSs to the allocated budget.…”

“…Considering the objective function (1) and the related constraints (2)- (20), the proposed model is formulated in MILP format which guarantees the global optimum solution of the problem in an effective runtime. The input data for solving the problem consists of network data, switch costs, MSs location, reliability assumptions, and study horizon.…”

Electric Power Systems Research

“…Usually, switch placement is formulated as a constrained nonlinear mix-integer optimization problem [67][68][69][70][71][72][73][74][75]. Heuristics, such as fuzzy logic approach [68], genetic algorithm [69], and immune algorithm [70], are used to obtain a near-optimal solution with acceptable computational performance.…”

Smart Distribution Systems

“…Usually, switch placement is formulated as a constrained nonlinear mix-integer optimization problem [67][68][69][70][71][72][73][74][75]. Heuristics, such as fuzzy logic approach [68], genetic algorithm [69], and immune algorithm [70], are used to obtain a near-optimal solution with acceptable computational performance.…”