Although the distributed generator (DG) placement and distribution network (DN) reconfiguration techniques contribute to reduce power loss, obviously the former is a design problem which is used for a long-term purpose while the latter is an operational problem which is used for a short-term purpose. In this situation, the optimal value of the position and capacity of DGs is a value which must be not affected by changing the operational configuration due to easy changes in the status of switches compared with changes in the installed location of DG. This paper demonstrates a methodology for choosing the position and size of DGs on the DN that takes into account re-switching the status of switches on distribution of the DN to reduce power losses. The proposed method is based on the runner root algorithm (RRA) which separates the problem into two states. In State-I, RRA is used to optimize the position and size of DGs on closed-loop distribution networks which is a mesh shape topology and power is delivered through more than one line. In State-II, RRA is used to reconfigure the DN after placing the DGs to find the open-loop distribution network which is a tree shape topology and power is only delivered through one line. The calculation results in DN systems with 33 nodes and 69 nodes, showing that the proposed method is capable of solving the problem of the optimal position and size of DGs considering distribution network reconfiguration.

This paper proposes a method for optimizing the location and size of Distributed Generators (DGs) based on the Coyote Algorithm (COA), in order to minimize the power loss in an Electric Distribution System (EDS). Compared to other algorithms, COA does not need control parameters during its execution. The effectiveness of COA was evaluated in an EDS with 33 nodes for two scenarios: the optimization of location and capacity of DGs in an initial radial configuration, and the best radial configuration for power loss reduction. Results were compared with other methods, showing that the proposed COA is a reliable tool for optimizing the location and size of DGs in an EDS.

Summary This article presents the problem of optimizing position and operating power of battery energy storage system (BESS) in the distribution system for the 24‐hour period. Wherein, the surveyed period is divided into small periods of peak, standard, and off‐peak hours. The goal is to find the optimal node for installation of BESS and its power in each interval to reduce the electricity purchasing cost and the cost of energy loss. The cuckoo search algorithm (CSA) is mapped to find the optimal parameters of BESS, and its efficiency is compared with that of genetic algorithm, sunflower optimization, and pathfinder algorithm. The efficiency of the proposed problem has been evaluated on two test systems. The obtained results show that the proposed problem and method have ability to reduce energy cost as well as contribute to reduce peak loads during peak hours in the 24‐hour period. The results also show that CSA is an effective tool for the problem of optimization position and power of BESS.

The distribution network reconfiguration (DNR) problem to minimize energy loss is one of complicate problem and studied more in the recently the year. In which, reconfiguration distribution network through the average branch power is showed method's effective is that simple, obtaining fast optimization results and even without using the load curve (for 24 hours). However, with high penetration of photovoltaic (PV) in the distribution network, the power flow on the branches at some survey time may change direction and leading to the average power on the branches can be zero but the energy loss is not minimal. Hence, determining accurately the average branch power in the case with PV participating grids is an important part for the problem of distribution network reconfiguration with PV connection to minimize energy loss. In order to solve this problem, an analytical technique based on load factor is presented in this paper for purpose of determining accurately the average power on the branches via determine the amount of additional power on the branch when PV is installed in the distribution power system. In addition, modified branch exchange method to quickly determine the configuration of the distribution network with PV achieving the smallest energy loss also is proposed in the paper. The proposed method is tested on the IEEE 18 node and IEEE 33 node distribution power system that shows the effectiveness of the proposed method compared with many other methods.

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