Network LOCATION models comprise one of the main categories of LOCATION models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network LOCATION problem, nodes represent demand points and candidate LOCATIONs to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility LOCATION Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility LOCATION and NDP (Network Design Problem). In previous studies, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and facility LOCATIONs with low utilization. Furthermore, facility LOCATION cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.

The purpose of this paper is OPTIMAL LOCATION of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index and voltage stability index with their relevant constraints, voltage constraints and transmittable power from the line. Load variation has been shown for three different time durations (peak, off peak and average).PSO technique has been used to optimize the objective function while Max-Min method has been applied to select the answer. Results produced from the proposed model have been provided in 5 different scenarios on a 33 bus system of IEEE.

This paper presents a fuzzy interactive approach to find the OPTIMAL LOCATION of OPTIMAL Unified Power Flow Controller (OUPFC) device as a multi-objective optimization problem. The problem formulation is based on OPTIMAL Power Flow (OPF) problem while the metric function and weighting method are added to ensure the collaboration among objective functions. The objective functions are the total fuel cost, power losses, and system loadability with and without the minimum cost of OUPFC installation. The proposed algorithm is implemented on IEEE 14- and 118-bus systems. The solution procedure uses nonlinear programming with discontinuous derivatives (DNLP) to solve the OPTIMAL LOCATION and settings of OUPFC device to enable power system dispatcher to improve the power system operation. The optimization problem is modeled in General Algebraic Modelling System (GAMS) software using CONOPT solver. Furthermore, the results obtained by OUPFC are compared with those of the Unified Power Flow Controller (UPFC) device. The OUPFC is outperformed by UPFC in the power system operation from the economic and technical point of view.