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The concept of electrical-mobility, in opposition to the present oil-mobility, is attracting the attention of politicians and of civil society worldwide. Electrical mobility means the usage of battery powered Electric Vehicle (EV) and Plug-in Hybrid Electric Vehicle (PHEV) as the main future technology to combat greenhouse gas emissions. The burden of electric mobility will be mainly on the distribution...
Demand response (DR) is becoming a key component of future smart grid that can reduce peak load and adapt elastic demand to fluctuating generations. While reducing energy bills for the participant, DR usually decreases its utility, which is different for distributed occupants inside a participating entity. A two-level distributed intelligent load management and control system is proposed in this paper...
This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators' use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable...
This paper presents a hybrid algorithm that combines Particle Swarm Optimization (PSO) and Nonlinear Optimal Power Flow (OPF) in the optimal sitting and sizing of Distributed Generation (DG). The objective function considered is to minimize the power losses in distribution systems. The proposed approach makes use of a sensitivity index based on derivatives to identify the best candidate buses for...
The proliferation of distributed generators (DGs) and the concept of microgrids have altered a distribution network from a passive network to an active one. Hence, active distribution power flow methods need to account for a DG unit, which can operate either as a PV or PQ bus. However, some of the existing active distribution power flow methods have difficulty to converge if the resistance-to-reactance...
There are a lot of uncertainties in planning and operation of electric power system, which is a complex, nonlinear, and non-stationary system. Advanced computational methods are required for planning and optimization, fast control, processing of field data, and coordination across the power system for it to achieve the goal to operate as an intelligent smart power grid and maintain its operation under...
In power systems, power quality issues raised by various non-linear devices (NLD) might violate the allowable harmonic limits defined by IEEE-519 standard. In order to maintain the total harmonic distortion well below the allowable limits, passive harmonic filters are commonly used. This paper presents an algorithm to optimally plan passive harmonic filters in the distribution networks to minimize...
This paper presents an application of heuristic optimization techniques such as Harmony Search Algorithm (HSA), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA) for efficient operation in micro grid. For operational efficiency, the objective function in a diesel generator consists of the fuel cost function similar to the cost functions used for the conventional fossil-fuel generating...
In this paper, population-based artificial intelligence techniques are explored to solve distribution network reconfiguration problem. The genetic algorithm, particle swarm optimization and ant colony optimization based methods already established by the authors are further modified to improve their performance and reduce computation time. All these methods are tested on six standard distribution...
The objectives of the movement toward the smart grid include making the power systems more reliable and economically efficient. The rapid development of the large scale energy storage technology, such as sodium sulfur batteries, makes it an excellent candidate in achieving the goals of the smart grid. This paper proposed a modified multi-objective particle swarm optimization approach to solve the...
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