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This paper provides a stochastic optimization algorithm for the planning of distribution system (DS) feeders. The algorithm finds the optimal feeder routing considering the stochastic variations of load demands (e.g., electric vehicle charging stations) as well as renewable-based distributed generators (DGs) (e.g., photovoltaic and wind DGs). The stochastic variations are addressed using a Monte-Carlo...
We present a test suite of 23 instances of a preventive maintenance scheduling problem from the power industry, which we also make available online. The formulation of the problem and the suite are derived from real-world data collected recently. A first study of the landscape characteristics of these problem instances based on three different types of adaptive walk reveals a generally rugged landscape,...
In this paper, a Genetic Algorithm (GA) based fuzzy goal programming (FGP) technique to multiobjective optimal planning of electric power generation and dispatch problem in power system operation and planning phases is presented. In the proposed approach, fuel cost, environmental emission and voltage deviation objectives of optimal power flow calculation are fuzzily described. In the solution process,...
A metaheuristic technique for solving the short-term transmission network expansion and reactive power planning problems, at the same time, in regulated power systems using the AC model is presented. The problem is solved using a real genetic algorithm (RGA). For each topology proposed by RGA an indicator is employed to identify the weak buses for new reactive power sources allocation. The fitness...
In this paper we propose and develop a heuristic methodology based in genetic algorithms to obtain the optimal placement and size of distributed generation in order to maximize the net benefit for the distribution utility's cost. Technical aspects like energy losses, voltage levels and reliability are considered, as well as economic aspects like price of energy, investment and operating cost of distributed...
Distributed generation (DG) sources are becoming more prominent in distribution systems due to increased demand for the electrical energy. The locations and capacities of DG sources will have an impact on system losses, voltage profile characteristics of distribution network. This paper presents a heuristic approach for selection of optimal location and determination of optimal capacity of DG sources...
This paper presents an efficient method for probabilistic distribution network expansion planning with Multi-objective Memetic Algorithm (MOMA) that combines Multi-objective GA with LS (local Search). Recently, the emergence of the deregulated and competitive power markets makes distribution networks more complicated. In this paper, a Monte-Carlo-Simulation (MCS) based method is proposed for handling...
This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering open access. The methodology finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with multiples generation scenarios. The model presented is solved using a specialized genetic algorithm. The methodology...
The latest political initiatives on energy saving are forcing distributors to implement actions that increase the energy efficiency of their system. Among these actions distributors can drive the development of the distributed generation (DG) on their networks. The inclusion of the energy saving goal among the terms of the objective function makes the DG allocation problem more and more complicated,...
With increasingly proportion of distributed generation (DG) in the power system, traditional power system planning has new challenges and demands. The necessity for flexible electric system, changing regulatory, energy savings and environmental impact are providing impetus to the development of DG. Itpsilas critical that the power system impacts be assessed accurately so that DG can be applied in...
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