The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes a new objective function for solving the optimal management of MicroGrid (MG) problem. This objective function aims to minimize MicroGrid's operating cost as well as the emissions of atmospheric pollutants while constraining it to meet the load demands. Some Objective constraints are presented in this paper for the safety of MG system. Moreover, the particle swarm-based-simulated...
This paper presents a fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solving the large economic power dispatch with non-smooth cost fuel functions. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules, the adaptive PSO executed in parallel based in decomposed network procedure as a local search...
This paper presents a new optimization algorithm, Music Based Harmony Search (MBHS) applied to the Optimal Power flow (OPF) problem with line constraints for minimizing the Fuel costs together with Generator Reactive power losses. The proposed method is compared with other optimization techniques like Simple Genetic Algorithm (SGA), Adaptive Genetic Algorithm (AGA) and Particle Swarm Optimization...
This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic...
This paper presents the use of Pareto optimization techniques that was previously analyzed with small scale power plant models where results could be verified analytically. Further research has been conducted into the use of applying these techniques to large scale models and analyzing performance. These approaches have been verified to scale well to larger applications. Through the use of multi-objective...
The energy management strategy renders significant impacts on the operating performance of plug-in hybrid electric vehicles (PHEV), which are similar to the traditional hybrid electric vehicle. A comprehensive methodology based on Particle Swarm Optimization (PSO) is presented in the paper to achieve parameter optimization for the energy management strategy, with a view to reducing the fuel consumption...
A new multi-objective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem based on Particle Swarm Optimization (PSO) is proposed in this paper. The new algorithm has adopted the maintenance method of Pareto candidate solution set based on the max-min distance density. The algorithm effectively guarantees the convergence of the algorithm and the diversity solutions. The performance...
The matching design problem of the ship-engine-propeller is a non-linear constrained multi-objective optimization problem which is performed based on multiple objectives,such as system efficiency and the life cycle cost. A multi-objective particle swarm optimization (MOPSO) approach for matching design problem of the ship-engine-propeller problem is presented in this paper.A real matching design problem...
This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called hybrid particle swarm optimization - differential evolution (PSO-DE). The mutation operators...
Hybrid fuel cell power plants have been introduced as an alternative power source for distributed generation, which can improve the power quality and reliability of the power grid. One of the most important issues of plant operations is the optimal control of the power plant, which will provide significant economic and environmental benefits in the long run. As a commercialized fuel cell technology,...
In this work, multi-objective optimization for design of a benchmark cogeneration system known as CGAM cogeneration system is performed. In optimization approach, the exergetic and economic aspects are considered, simultaneously. The thermoeconomic objective is minimized while the exergetic objective is maximized. A multi-objective particle swarm optimization (MOPSO) algorithm is used to find a set...
Ship design is a complex endeavor requiring the successful coordination of many different disciplines. According to various disciplines requirements, how to get a balanced performance is imperative in ship design. Thus, a all-in-one Multidisciplinary Design Optimization (MDO) approach is proposed to get the optimum performance of the ship considering three disciplines, structure; cargo loads and power...
An automatic Vehicle-to-Grid (V2G) technology can contribute to the utility grid. V2G technology has drawn great interest in the recent years. Success of the sophisticated automatic V2G research depends on efficient scheduling of gridable vehicles in constrained parking lots. Parking lots have constraints of space and current limits for V2G. However, V2G can reduce dependencies on small expensive...
Vehicle-to-Grid (V2G) technology has drawn great interest in the recent years. Success of the V2G research depends on efficient scheduling of gridable vehicles in limited parking lots. V2G can reduce dependencies on small expensive units in the existing power systems as energy storage that can decrease running costs. It can efficiently manage load fluctuation, peak load; however, it increases spinning...
This paper presents particle swarm optimization (PSO) technique to solve economic dispatch of valve-point loaded generating units considering emission constraint. This problem has gained recent attention due to the deregulation of power industry and environmental regulations. Minimizing operating cost can no longer be the only criterion for dispatching electric power due to increasing concern over...
In this paper, a new technique based on particle swarm optimization (PSO) is proposed to incorporate voltage stability limits into traditional optimal power flow (OPF) formulations. Two objective functions such as fuel cost and voltage stability margin (loadability) are considered to be optimized. In proposed method systempsilas maximum loading margin (loadability) is calculated by continuation power...
Plug-in hybrid electric vehicles (PHEVs) differ from hybrid electric vehicles (HEVs) with their ability to use off-board electricity generation to recharge their energy storage systems. In addition to possessing charge-sustaining HEV operation capability, PHEVs use the stored electrical energy during a charge-depleting (CD) operating period to displace a significant amount of petroleum consumption...
This paper presents a novel modified bacterial foraging technique (BFT) to solve economic load dispatch (ELD) problems. BFT is already used for optimization problems, and performance of basic BFT for small problems with moderate dimension and searching space is satisfactory. Search space and complexity grow exponentially in scalable ELD problems, and the basic BFT is not suitable to solve the high...
This paper presents a modified particle swarm optimization (MPSO) algorithm for solving the optimal power flow (OPF) problems. The main distinction of this approach is in using particlepsilas worth experience in stead of the best previous experience. The proposed approach is evaluated on the IEEE 30-bus test system which minimizes the total fuel cost considering operational constraints such as power...
Some problems are known to have computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs portfolio of intelligent systems algorithms for optimising a metal reheat furnace scheduling problem. The proposed system has been evaluated for different techniques...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.