Showing papers in "International Journal of Electrical Power & Energy Systems in 2013"

TL;DR: In this paper, a full scope review of the principal energy storage technologies being developed so far, and the features and benefits of energy storage systems (ESSs) within the MG are analyzed in details including ESS configuration and topologies, power electronics interfaces, ESS control schemes for charging/discharging, control strategy of hybrid ESS as well as optimization of the renewable sources and ESS.

TL;DR: The particle swarm optimization (PSO) technique has been used to solve the optimal placement of DGs and the optimal power factor for DG supplying, both real and reactive power, has been obtained.

TL;DR: A new evolutionary method called Teaching–Learning Based Optimization (TLBO) algorithm has been presented, which is modified and used in this paper to find the best sites to connect DG systems in a distribution network, choosing among a large number of potential combinations.

TL;DR: In this article, a two area thermal system with governor dead-band nonlinearity is considered for the design and analysis purpose and differential evolution (DE) algorithm based on parallel 2-Degree Freedom of Proportional-Integral-Derivative (2-DOF PID) controller for Load Frequency Control (LFC) of interconnected power system is presented.

TL;DR: In this article, a new constrained multi-objective Particle Swarm Optimization (PSO) based wind Turbine Generation Unit (WTGU) and photovoltaic (PV) array placement approach for power loss reduction and voltage stability improvement of radial distribution system is proposed.

TL;DR: In this article, an efficient technique is presented for optimal placement and sizing of distributed generation (DG) sources in a large scale radial distribution system to minimize network power losses and to improve the voltage stability.

TL;DR: In this paper, an Artificial Bee Colony (ABC) algorithm is employed as the main optimizer for optimal adjustments of the power system control variables of the OPF problem, which involves both continuous and discrete variables.

TL;DR: In this article, a method based on analytical approach for optimal allocation (sizing and siting) of DG and capacitor with the objective to minimize the total real power loss subjected to equality and inequality constraints in the distribution network is presented.

TL;DR: The application of Teaching Learning Based Optimization (TLBO) algorithm for optimal coordination of DOCR relays in a looped power system is discussed and the proposed algorithm TLBO gives optimal coordination margin between 0.3 and 0.8 s and no miscoordination between primary and backup pairs.

TL;DR: In this paper, an application of the novel artificial intelligent search technique to find the parameters optimization of nonlinear Load Frequency Controller (LFC) considering Proportional Integral Derivative controller (PID) for a power system is presented.

TL;DR: In this article, a comparison of novel, combined loss sensitivity, index vector, and voltage sensitivity index methods for optimal location and sizing of distributed generation (DG) in a distribution network is presented.

TL;DR: Results demonstrate superiority in terms of solution quality of the proposed QOTLBO approach over original TLBO and other optimization techniques and confirm its potential to solve the ORPD problem.

TL;DR: A probabilistic Price Based Unit Commitment (PBUC) approach using Point Estimate Method (PEM) is employed to model the uncertainty in market price and generation sources, for optimal bidding of a VPP in a day-ahead electricity market.

TL;DR: A novel approach based on cuckoo search which is applied for optimal distributed generation (DG) allocation to improve voltage profile and reduce power loss of the distribution network is presented.

TL;DR: To solve the complicated nonlinear, non-smooth, and non-differentiable SDEED, an enhanced particle swarm optimization (PSO) algorithm is applied to obtain the best solution for the corresponding scenarios to improve the quality of the solutions attained by PSO.

TL;DR: In this article, a teaching learning based optimization (TLBO) algorithm is proposed to solve short-term hydrothermal scheduling (HTS) problem considering nonlinearities like valve point loading effects of the thermal unit and prohibited discharge zone of water reservoir of the hydro plants.

TL;DR: In this paper, the particle swarm optimization (PSO) based loop shaping of H-infinity controller is used and compared with those obtained by genetic algorithm (GA) to minimize the frequency deviation.

TL;DR: This investigation presents a SVR-based electric load forecasting model which applied a novel hybrid algorithm, namely chaotic genetic algorithm (CGA), to improve the forecasting performance, and results indicate that the proposed model yields more accurate forecasting results than ARIMA and TF-e-SVR-SA models.

TL;DR: The superiority of the proposed NSGA-II optimized PI/PID controllers has been shown by comparing the results with some recently published modern heuristic optimization approaches such as Bacteria Foraging Optimization Algorithm, Genetic Algorithm and Craziness based Particle Swarm Optimization for the similar interconnected power systems.

TL;DR: In this article, a multi-objective approach to determine optimal site and size of parking lots, which provide vehicle to grid (V2G) power in distribution system as new type of distributed generations (DGs), is presented.

TL;DR: In this article, a comprehensive survey of different issues associated with integration of doubly fed induction generators (DFIG) based system into the grid is presented in the context of wind turbine energy generation.

TL;DR: In this paper, the authors evaluate the effect of progressive aluminum wire rupture on the temperature profile of an ACSR (Aluminum Conductor Steel Reinforced) overhead electrical conductor, not only on the section of the damage but also along the length of the conductor.

TL;DR: In this article, a differential harmony search (DHS) algorithm is proposed by combining the mechanisms of both differential evolution and harmony search, and the pitch adjustment operation is cooperated with the different mutation operation to enhance the exploitation ability of harmony search.

TL;DR: In this article, a non-dominated sorting QOTLBO is employed to approximate the set of Pareto solution through the evolutionary optimization process to obtain EED solution for 6-unit, 10-unit and 40-unit systems.

TL;DR: In this paper, an economic emission load dispatch (EELD) problem is solved to minimize the emission of nitrogen oxides (NOX) and fuel cost, considering both thermal generators and wind turbines.

TL;DR: The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum, making the solution process much quicker.

TL;DR: The proposed solution involves a class of Adaptive Critic Designs (ACDs) called Action Dependent Heuristic Dynamic Programming (ADHDP) that uses two neural networks, namely the Action and the Critic Network that is able to minimize a given Utility Function over a certain time horizon.

TL;DR: In this paper, an optimal operation of a grid-connected variable speed wind turbine equipped with a Doubly Fed Induction Generator (DFIG) is presented, where a cascaded nonlinear controller is designed to perform two main objectives.

TL;DR: In this article, an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method is presented, where the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change.

TL;DR: Compared with differential evolution, evolutionary programming and real coded genetic algorithm, the proposed algorithm seems to be a promising alternative approach for solving the MAED problems in practical power system.