فهرست مقالات Improved particle swarm optimization

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  1 - Load Frequency Control in Power Systems Using Improved Particle Swarm Optimization Algorithm
  Milad Babakhani Qazijahan
  The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has چکیده کامل

  The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has a longer settling time and a lot of Extramutation in output response of system so it required that the parameters be adjusted as appropriate . In thispaper, we aim to design a system based on PI controllers using improved particle swarm optimizationalgorithm for load frequency control .Multi-population approach and local search to improve theoptimization algorithms is used and displayed. That this approach will lead to accelerating the achievementof results, preventing entrapment in a local minimum, and get better system output compared with similarmethods. پرونده مقاله
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  2 - An Improved Particle Swarm Optimization Algorithm for Energy Management in Distribution Grid Considering Distributed Generators
  Hossein Lotfi Reza Ghazi Mohammad Bagher Naghibi Sistani
  This study proposes, a novel approach for optimal energy management’s problem and capacitor switching in the distribution network at the presence of distributed generators, energy storage units and solar photovoltaic arrays. Modern distribution networks, in additi چکیده کامل

  This study proposes, a novel approach for optimal energy management’s problem and capacitor switching in the distribution network at the presence of distributed generators, energy storage units and solar photovoltaic arrays. Modern distribution networks, in addition to the importance of economic issues, must operate at an acceptable level of system reliability, Failure to pay attention to the reliability importance can lead to irreparable damages in the distribution network. Toward this end, energy not supplied as a reliability index along with operation cost are considered as objective functions. Also, the effect of uncertainty resources related to solar photovoltaic arrays power generation and electricity price are considered in the optimization problem evaluations. Considering the effects of distributed generators and energy storage units causes the proposed problem more be complicated, for this reason, an improved particle swarm optimization algorithm is provided to deal the complexity of the problem. The proposed algorithm is tested in the IEEE 33-node test system, and its superiorities are shown through comparison with other evolutionary algorithms. پرونده مقاله
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  3 - A new hybrid algorithm for multi-objective distribution feeder reconfiguration considering reliability
  hossein lotfi
  Reducing electricity losses is the main objective in distribution feeder reconfiguration (DFR) problem. Distribution feeder reconfiguration is an optimization problem in power system which is performed through changing switching state. In this study, distribution feeder چکیده کامل

  Reducing electricity losses is the main objective in distribution feeder reconfiguration (DFR) problem. Distribution feeder reconfiguration is an optimization problem in power system which is performed through changing switching state. In this study, distribution feeder reconfiguration is optimized in the presence of distributed generators (DGs). In common DFR problems, reliability constraint is not satisfied and power losses or voltage deviation of buses is selected as the objective function. In this study, multi-objective problem is considered as a combination of reliability along with power losses. By adding reliability, the problem becomes more complex and requires an accurate method for solving multi-objective optimization problem. For this purpose, in this paper proposed a new hybrid evolutionary algorithm for solving the DFR problem. The proposed hybrid evolutionary algorithm is the combination of PSO (particle swarm optimization) and SFLA (shuffled frog leaping algorithm), called Improved particle swarm optimization (IPSO). In order to investigate efficiency of the proposed method, two 33-bus and 70-bus test systems are tested and the results are compared with GA and PSO algorithms پرونده مقاله
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  4 - Optimization of grid independent diesel-based hybrid system for power generation using improved particle swarm optimization algorithm
  Akbar Maleki Fathollah Pourfayaz
  The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for elec چکیده کامل

  The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for electrification to an off-grid remote area located in Rafsanjan, Iran. For this location, different hybrid systems are studied and compared in terms of cost. For cost analysis, a mathematical model is introduced for each system's component and then, in order to satisfy the load demand in the most cost-effective way, particle swarm optimization algorithm are developed to optimally size the systems components. As an efficient search method, IPSO has simple concept, is easy to implement, can escape local optima, by use of probabilistic mechanisms, and only needs one initial solution to start its search. Simulation results indicate that, the role of the diesel generator decreases in hybrid (PV/wind/diesel/battery) energy systems پرونده مقاله
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  5 - Solving Economic Dispatch in Competitive Power Market Using Improved Particle Swarm Optimization Algorithm
  Hossein Lotfi Ali Dadpour Mahdi Samadi
  IJSEE-1705-1054
  Generally the generation units in the traditional structure of the electricity industry try to minimize their costs. However, in a deregulated environment, generation units are looking to maximize their profits in a competitive power market. Optimum generation planning چکیده کامل

  Generally the generation units in the traditional structure of the electricity industry try to minimize their costs. However, in a deregulated environment, generation units are looking to maximize their profits in a competitive power market. Optimum generation planning in such structure is urgent. This paper presents a new method of solving economic dispatch in the competitive electricity market with the aim of maximizing the total contribution profit of power generation. In this regard, with a combination of two intelligent optimizations, a new efficient algorithm which called improved particle swarm optimization algorithm is suggested. The simulation of the new approach and conventional PSO algorithm were performed on two case study systems, 10-units and 15-units. According to the results, the suggested method not only resolves the convergence problem, but it also makes more efficient response. پرونده مقاله