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This paper aims presenting a methodology for economic dispatch (ED) of island grids with distributed energy resources (DERs). The method utilizes an algorithm dedicated to battery storage systems (BSSs) placement optimization in a given power system using genetic algorithms (GA), where daily time varying loads, wind power generations, and diesel power generator operation scheduling are considered...
The increasing penetration of renewable generation poses a challenge to the power system operator's task of balancing demand with generation due to the increased inter-temporal variability and uncertainty from renewables. Recently major system operators have been testing approaches to managing inter-temporal ramping requirement. In this paper we propose a robust optimization based economic dispatch...
The practical economic dispatch (ED) problems have many non-convex characteristics, which makes the searching of the global optimum difficult when using traditional mathematical methods. This paper presents a novel hybrid algorithm (HA) to the ED problems based on the particle swarm optimization (PSO) technique and differential evolution (DE) algorithm. Since the standard PSO has the adversity of...
The purpose of this work is to apply a hybrid algorithm based on Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) for solving the problem of Economic Dispatch, which is based on supplying an energy demand, subjected to some restriction and reach out the best possible cost. Basically, we use the mutation operator from GAs aiming to explore regions in the search space that cannot be reached...
The appropriate dispatch of Load Shifting Devices (LSD) and Renewable Energy Sources (RES) is still a challenging issue for the Remote Community (RC). This paper analyzes three techniques for the economic dispatch of a RC microgrid that implements RES and LSDs as in the case of Energy Storage Systems (ESS) to a diesel infrastructure. Two online or period-ahead techniques are compared to an offline...
The location of a wind turbine is fundamental to enhance its performance. However, there are other factors that should be taken into account when deciding the best position for a wind turbine. This paper presents the influence of a wind penetration sitting in different distribution networks for the optimization of the economic dispatch problem. A genetic algorithm is developed to solve this problem...
Peak load management is one of the important challenges faced by the power industry, in terms of both frequency management and economic aspects of scheduling the generating units. Pumped storage hydro electricity (PSH) plants are the most opted plants, to act as peak load power plant, because of their quick response. When group of PSH plants are present, scheduling of each plant's operating point...
Global electricity demand has been growing very rapidly to meet the needs of modern civilization for uninterrupted supply of electricity. Therefore an efficient operating policy for committed units (CUs), in order to meet the load demand is very important for power utility operators. Economic Dispatch (ED) problem helps to find a suitable operating policy to reduce the fuel cost for CUs without violating...
The economic dispatch problem deals with minimization of cost of producing electrical power demanded by power system. The penetration of wind power in power systems is increasing worldwide due to environmental constraints and fossil fuel depletion. The main difficulty, however, is accurate prediction of wind power which otherwise may lead to situation in network operation. For more safe and reliable...
This paper presents a modified Firefly Algorithm (MFA) for solving economic dispatch (ED) problems. ED is one of the most challenging problems of power system since it is difficult to determine the optimum generation scheduling to meet the particular load demand with the minimum fuel costs while all constraints are satisfied. In addition the practical ED problems which are involving objective functions...
With the in-depth development of smart grid, renewable energy, such as wind power, will be an important source of electrical energy, the proportion of renewable resources increase rapidly. Serious problems emerged with large-scale wind power integrating to power grid. The integration of wind generation imports variability and uncertainty to system operation and control. Control center must consider...
Microgrids are operated by a customer or a group of customers for having a reliable, clean and economic mode of power supply to meet their demand. Understanding the economics of system is a prime factor which really depends on the cost/kWh of electricity supplied. This paper presents an easy and simple method for analyzing the dispatch rate of power. An isolated microgrid with solar and wind is considered...
This paper proposes security constrained economic power dispatch (SCED) of the generators using parallel artificial bee colony (PABC) algorithm for electricity markets. The proposed non-linear optimization problem considers simultaneous minimization of deviations from scheduled transactions and minimization of fuel cost of the generators. The problem is formulated as a constrained optimization problem...
Particle swarm optimization (PSO) has attracted interest in recent years to solve practical economic dispatch problems. However, as with traditional optimization methods, conventional PSO may converge to local optima and incurs significant computational overheads to produce a practical solution, and has a performance which strongly depends on the choice of internal parameters. To address these drawbacks,...
The replicator dynamics model is an evolutionary game concept that describes the state of a population in a process inspired by natural selection. This model is used to analyze a resource allocation problem in distributed networked systems. The main properties of the replicator equation are analyzed to propose a novel technique based only on the available information of a system modeled as a connected...
This paper presents a new approach to emission constrained generation scheduling model based on cost optimization. The combined economic and emission dispatch is non-linear optimization problem with several constraints (economic and environmental) subject to reduce the emission of harmful pollutants and the operating cost of the thermal power plant. In this paper the problem of combined economic and...
The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics...
To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization...
This paper presents an Improved Parallel Differential Evolution (IPDE) optimization algorithm based dynamic decomposed strategy to solving large economic dispatch (ED) with consideration of practical generators constraints. The migration operation inspired from Biogeography-based Optimization algorithm (BBO) is newly introduced in the parallel DE approach, thereby can effectively explore and exploit...
This paper proposes a method to determine the output of all online units with minimum total cost when the amount of emission is reasonable. A joint economic and emission dispatch is proposed in order to get a significant compromise between costs and emission such that real power supply-demand equilibrium is satisfied. In order to have a meaningful compromise between costs and emission in the problem...
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