Simultaneous Multi-area Economic-Environmental Load Dispatch Modeling in Presence of Wind Turbines by MOPSO (original) (raw)
Related papers
2015
The economic load dispatch (ELD) represents one of the basic functions of power system operation and planning. In general, the task of ELD is to allocate optimally loads among on-line generating units in order to minimize the total operational cost subject to power balance, system reserve requirements and other system constraints. Renewable energy resources such as wind power have significant attention in recent years in power system field. It takes part to minimize the fuel consumption in the thermal units. This paper presents the influence of a wind turbine location on the optimization of ELD problem. The particle swarm optimization (PSO) technique is presented to solve this problem. The performance of the presented method is evaluated using two standard systems, and compared with two published methods. The first is evolutionary represented by the genetic algorithm (GA) and the second is determinist represented by the interior point (IP). In addition, a comparison between results ...
Particle Swarm Optimization for Solving the Economic Load Dispatch Including Wind Energy
Economic load dispatch among thermal units is one of the most important problems in power systems operation. Usually so called equal marginal cost criterion is adopted to this calculation. Recently global trend of utilizing more and more renewable energy such as wind power makes this problem more important than ever. With the continuing search for alternatives to conventional energy sources, it is necessary to include wind energy generators (WEG) in the ELD problem. This paper presents a solution of economic load dispatch incorporation wind energy using a particle swarm optimization algorithm (PSO). The effect of wind energy generators system inclusion on ELD problem is investigated, with the source wind susceptible to short duration variations, which is the uncertainty of wind speed around a short-duration-stable mean value. A six unit test system is resolved using PSO to illustrate the variation in the optimal cost, losses, and system-λ with the variation of short-duration-stable ...
Engineering, Technology & Applied Science Research, 2021
Power dispatch has become an important issue due to the high integration of Wind Power (WP) in power grids. Within this context, this paper presents a new Particle Swarm Optimization (PSO) based strategy for solving the stochastic Economic Emission Dispatch Problem (EEDP). This problem was solved considering several constraints such as power balance, generation limits, and Valve Point Loading Effects (VPLEs). The power balance constraint is described by a chance constraint to consider the impact of WP intermittency on the EEDP solution. In this study, the chance constraint represents the tolerance that the power balance constraint cannot meet. The suggested framework was successfully evaluated on a ten-unit system. The problem was solved for various threshold tolerances to study further the impact of WP penetration.
Journal of The Institution of Engineers (India): Series B, 2019
In this paper, three important objectives of power systems-cost of generation (FC), system transmission losses (FL) and environmental emissions (FE)have been considered. The multiobjective economic load dispatch problem has been formulated using weighting method. The noninferior set for IEEE 5 bus, IEEE 14 bus and IEEE 30 bus systems has been generated using particle swarm optimization technique. The noninferior set obtained has been displayed in 3-D space considering all the three objectives and in 2-D space all the combinations of two objectives, viz. for FC & FL, FC & FE and FL & FE for IEEE 5 bus, IEEE 14 bus and IEEE 30 bus systems. The target point or best compromise solution has been obtained by maximizing the minimum relative attainments of all the objectives.
Sustainability
In recent years, wind energy has been widely used as an alternative energy source as it is a clean energy with a low running cost. However, the high penetration of wind power (WP) in power networks has created major challenges due to their intermittency. In this study, an elitist multi-objective evolutionary algorithm called non-dominated sorting particle swarm optimization (NSPSO) is proposed to solve the dynamic economic emission dispatch (DEED) problem with WP. The proposed optimization technique referred to as NSPSO uses the non-dominated sorting principle to rank the non-dominated solutions. A crowding distance calculation is added at the end of all iterations of the algorithm. In this study, WP is represented by a chance-constraint which describes the probability that the power balance cannot be met. The uncertainty of WP is described by the Weibull distribution function. In this study, the chance constraint DEED problem is converted into a deterministic problem. Then, the NSP...
The Economic Dispatch for Integrated Wind Power Systems Using Particle Swarm Optimization
arXiv (Cornell University), 2015
The economic dispatch of wind power units is quite different from that in conventional thermal units; since the adopted model should take into consideration the intermittency nature of wind speed as well. Therefore, this paper uses a model that takes into account the aforementioned consideration in addition to whether the utility owns wind turbines or not. The economic dispatch is solved by using one of the modern optimization algorithms: the particle swarm optimization algorithm. A 6-bus system is used and it includes wind-powered generators besides to thermal generators. The thorough analysis of the results is also provided.
This paper describe about the optimization of economic loading dispatch (ELD) problem. Economic loading dispatch is one of the important optimization tasks which provide economic condition for a power system. The ELD problems have non-smooth objective function with equality and inequality constraints. This paper presents particle swarm optimization (PSO) method for solving the economic dispatch(ED) problem in power system. The particle swarm optimization is an efficient and reliable evolutionary computational technique, which is used to solve economic load dispatch with line power flows. This paper describes, a new PSO framework used to deal with the equality and inequality constraints in ELD problem. The proposed PSO can always provide satisfying results within a realistic computation time. The PSO is applied with non-smooth cost function. The six thermal units, 26 buses and 46 transmission lines system is used in this paper. The proposed PSO method results are compared with the genetic algorithm (GA) and conventional method to show the effectiveness of PSO method to solve the ELD problems in power system.
This paper deals with the problems of Economic Dispatch, Emission Dispatch and Combined Economic and Emission Dispatch problems for an integrated system having thermal and wind units. Particle Swarm Optimization and Genetic Algorithm methods are used to solve the problems of Economic dispatch, Emission dispatch and Combined Economic and Emission Dispatch problems. The effectiveness of PSO and GA methods are demonstrated by comparing the results obtained with both the methods.
Economic Dispatch Problem Solution Including Wind Energy Using PSO
Economic load dispatch among thermal units is one of the most important problems in power systems operation. Usually so called equal marginal cost criterion is adopted to this calculation. Recently global trend of utilizing more and more renewable energy such as wind power makes this problem more important than ever. With the continuing search for alternatives to conventional energy sources, it is necessary to include wind energy generators (WEG) in the ELD problem. This paper presents a solution of economic load dispatch incorporation wind energy using a particle swarm optimization algorithm (PSO). The effect of wind energy generators system inclusion on ELD problem is investigated, with the source wind susceptible to short duration variations, which is the uncertainty of wind speed around a short-duration-stable mean value. A 6 and 20 unit test system is resolved using PSO to illustrate the variation in the optimal cost, losses, and system-λ with the variation of short-duration-st...