Showing papers in "International Journal of Electrical Power & Energy Systems in 2014"

TL;DR: In this article, the authors reviewed the fundamentals and main concept of virtual synchronous generators (VSGs) and their role to support the power grid control, and focused on the poetical role of VSGs in the grid frequency regulation task.

TL;DR: In this article, the authors present a comprehensive study on Smart Grid and the role of Advanced Metering Infrastructure (AMI) in SG, which is not a single technology; rather it is a combination of different areas of engineering, communication and management.

TL;DR: In this article, the authors present an overall review of the modeling, planning and energy management of a combined cooling, heating and power (CCHP) microgrid with distributed cogeneration units and renewable energy sources.

TL;DR: In this paper, an artificial neural network-based battery model is developed to estimate the battery's state of charge (SOC) based on the measured current and voltage, which is validated using LiFePO4 battery data collected from the Federal Driving Schedule and dynamical stress testing.

TL;DR: In this paper, the authors examined and compared some machine learning regression methods to develop a predictive model, which can predict hourly full load electrical power output of a combined cycle power plant.

TL;DR: In this article, an efficient stochastic framework is proposed to investigate the effect of uncertainty on the optimal operation management of MGs, which considers the uncertainties of load forecast error, wind turbine (WT) generation, photovoltaic (PV) generation and market price.

TL;DR: In this article, the authors presented controller parameters tuning of differential evolution (DE) algorithm and its application to Load Frequency Control (LFC) of a multi-source power system having different sources of power generation like thermal, hydro and gas power plants.

TL;DR: In this article, a cost-based formulation to determine the optimal size of the battery energy storage (BES) in the operation management of the micro-grid is presented. And the performance of the approach is evaluated by one grid-connected low voltage MG where the optimal BES is determined professionally.

TL;DR: Fireworks Algorithm is used to simultaneously reconfigure and allocate optimal DG units in a distribution network using a new swarm intelligence based optimization algorithm conceptualized using the fireworks explosion process of searching for a best location of sparks.

TL;DR: In this article, a teaching learning based optimization (TLBO) approach is proposed to minimize power loss and energy cost by optimal placement of capacitors in radial distribution systems, where learners improve their knowledge or ability through the teaching methodology of teacher and in second part learners increase their knowledge by interactions among themselves.

TL;DR: A new Meta-heuristics Fireworks Algorithm is proposed to optimize the radial distribution network while satisfying the operating constraints and it is observed that the performance of proposed method is better than the other methods in terms of quality of solutions.

TL;DR: The results demonstrate that the adoption of demand response programs can reduce total operation costs of a microgrid and determine a more efficient use of energy resources.

TL;DR: A novel quasi-oppositional teaching learning based optimization (QOTLBO) methodology in order to find the optimal location of distributed generator to simultaneously optimize power loss, voltage stability index and voltage deviation of radial distribution network is presented.

TL;DR: In this paper, a method for determining the optimal size of a battery energy storage system (BESS) for primary frequency control of a microgrid is presented, by considering overloading characteristics and limitations of the state of charge (SOC) of battery.

TL;DR: In this article, the authors investigated the impact of DERs and effect of wind, price and demand uncertainties on total hub operation costs and hub reliability and also on which technology most be operated.

TL;DR: In this article, a particle swarm optimization algorithm for finding the optimal location and sizing of DSTATCOM with the aim of reducing the total power loss along with voltage profile improvement of Radial Distribution System is proposed.

TL;DR: An effective biologically inspired algorithm (Immune Algorithm) is used to search the best location and determine the size of DSTATCOM and minimum cost of installation and maximum power loss reduction are integrated into an objective function through appropriate weighting factors.

TL;DR: In this article, the authors proposed a methodology to solve Mixed Integer Non-Linear Programming (MINLP) formulation for loss minimization, which simplifies the problem by dividing it in two phases, namely Siting Planning Model (SPM) and Capacity Planning Model(CPM) thereby reducing the search space and computational time.

TL;DR: A novel hybrid particle swarm optimization and gravitational search algorithm (HPSO–GSA), having attributes of PSO and GSA, is proposed in this paper to solve economic emission load dispatch (EELD) problems considering various practical constraints.

TL;DR: Through the simulation of MATLAB programming it is seen that OTLBO provides better results than all other optimization techniques at less computational time.

TL;DR: In this article, an opposition-based gravitational search algorithm (OGSA) is applied for the solution of optimal reactive power dispatch (ORPD) of power systems, which is defined as the minimization of active power transmission losses by controlling a number of control variables such as generator voltages, tap positions of tap changing transformers and amount of reactive compensation.

TL;DR: In this article, an efficient hybrid method based on ICA and GA was proposed for optimal placement and sizing of DG sources and capacitors banks simultaneously to reduce power loss, improving system voltage profile, increasing voltage stability index, load balancing and transmission and distribution relief capacity for both utilities and the customers.

TL;DR: In this paper, a methodology for the integration of dispatchable and non-dispatchable renewable distributed generation (DG) units for minimizing annual energy losses is presented, where analytical expressions are first proposed to identify the optimal size and power factor of DG unit simultaneously for each location for minimizing power losses.

TL;DR: In this article, a new and efficient krill herd algorithm (KHA) was proposed to solve both convex and non-convex ELD problems of thermal power units considering valve point loading, multiple fuel operation, transmission losses and constraints such as ramp rate limits and prohibited operating zones.

TL;DR: In this article, a Two-Degree-of-freedom-Fractional Order PID (2-DOF-FOPID) controller is proposed for automatic generation control (AGC) of power systems.

TL;DR: In this article, a framework for reliable microgrid energy management based on receding horizon control is proposed, which allows taking into consideration cost values, power consumption and generation profiles, and specific constraints.

TL;DR: In this article, the authors proposed an efficient approach for evolutionary algorithm based Optimal Power Flow (OPF), which uses the concept of incremental power flow model, based on sensitivities.

TL;DR: The effectiveness and excellence of proposed stochastic bidding strategy of microgrid in a joint day-ahead market of energy and spinning reserve service is proven by comparing simulation results with traditional deterministic bidding strategy.

TL;DR: An autonomous smart charging framework that ensures both the stability of the power grid and customer savings is proposed that can be used to implement both energy storage and appliance scheduling schemes.