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An optimization method is proposed for the geometric parameters of an convergent nozzle ejector in the anode gas recirculation system in PEM fuel cell in this paper. The mathematical model of ejector is established by employing the hydrodynamics, thermodynamic principles and chemical constraints. An optimization method is applied based on hybrid fish swarm algorithm to optimize the geometry parameters...
This paper elucidatesa new improved optimization algorithm for economic Load dispatch (ELD) problem using self-adaptive real coded genetic algorithm. The ELD dilemma is formulated as a single-objective on-linear constrained optimization problem gratifying both equality and inequality constraints. The regeneration of population practice is integrated to the conventional real coded genetic algorithm...
The mean variance mapping optimization technique (MVMO) is employed in this paper to solve the economic dispatch problem (ED) in power systems. The effectiveness of the proposed technique has been verified on three different case studies to solve the ED problem of thermal power units taking into account the transmission losses and other constraints which include generation limits, ramp rate limits,...
This paper presents an application of Genetic Algorithm (GA) to solve Economic Load Dispatch problem which aims to determine minimum fuel cost and Environmental Load Dispatch problem which aims to determine minimum gas emission for required energy production of the chosen power system. Test system is chosen as IEEE-30 bus system which includes 6 generators with necessary values given for ease of simulation...
Based on the optimization design, the mathematical model of the control strategy parameter optimization taking the minimum fuel consumption as the objective function is established. Then, taking hybrid bulldozer as an example, the genetic algorithm is used to solve the optimization problem. Through optimization, the fuel consumption reduces 4.1% further more compared with conventional bulldozer under...
Nowadays the amount of electrical power generated on-board ships is drastically increased, especially for the All Electric Ships (AES) where all the energy needed is supplied by the electrical power system. In this context, the traditional methods to calculate the power demand and select the size of the generation system have become inadequate, since they are based on very dated assumptions. Aim of...
This paper proposes biogeography based optimization (BBO) algorithm and genetic algorithm (GA) to solve the unit commitment problem incorporating the wind energy (UCIW) uncertainty. Unit commitment (UC) problem is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints...
The Distributed Generation (DG) systems of today face a multitude of problems, among which the pollutant emissions and the energy efficiency play a key role. In this sense, the study of optimal operation strategies for such systems becomes highly important. Thus, the purpose of this work will be to investigate using the Nondominated Sorting Genetic Algorithm II (NSGA II) the operation of a 4 gas microturbine...
To date, one of the main issues addressed by numerous studies in maritime transport is the time needed for vessels to be served in the quay. On the other hand, not as many studies focus on how to minimize quay crane fuel consumption and eventually the costs related to these activities. This paper focuses on the integration of quay side operations and more specifically, the Quay Crane Scheduling Problem...
This paper demonstrates the use of a classical Case-Based Reasoning (CBR) approach applied to the automatic train conduction scenario. We use a CBR model, where the adaptation task consists on a multi-objective optimization approach. To realize the case study we have used a train simulator. It is capable of conducting a train in a pre-defined railway providing relevant data about the conduction, such...
This paper presents using the Bees algorithm approach to multi-objective optimal economic dispatch of electrical power systems. The generation of electricity from the fossil fuel releases several contaminants, such as sulfur oxides, nitrogen oxides and carbon dioxide, into the atmosphere. Genetic algorithmic approach to power system optimization, as reported here for a case of economic power dispatch,...
With the growth of commercial world, the utilization of electrical energy is also increased. Due to this the need to install large amount of power generation to meet the increasing load has become the basic utility, which is quite complex to distribute the power among large number of units economically in less time. This intricacy made to develop the faster convergent techniques to large systems....
Economic load dispatch problem becomes complex, when renewable energy sources are also considered with thermal power plant. Therefore, it is challenging to find the optimal solution at lower fuel cost, such that generation meets the load demand. This paper is mainly aimed to design economic load dispatch model for thermal and wind power plants. Due to the varying nature of wind speed, probabilistic...
This paper proposed an economic dispatch scheme based on stochastic frame. Compared with conventional dispatch, the stochastic dispatch fully considers the variation of distributed load variations in the grid between dispatch intervals. The objective function of the stochastic dispatch scheme aims to minimize the distribution of fuel cost rather than a single value. Due to the stochastic analysis,...
This paper presents optimal generation scheduling for minimization of fuel consumption (FC) in an offshore support vessel with a dynamic positioning system and diesel generator (DG) sets of 8000 kW total capacity. FC is analyzed for equal load sharing among equal capacity DGs, optimal load sharing among equal capacity DGs, and optimal load sharing among unequal capacity DGs. Due to nonlinear specific...
Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization...
This paper presents an overview of optimization field in case of condensing power plant. Different parameters of power system such as power losses, voltage drop, optimal placement, volume of generators, etc. were considered here; the analysis of their impact on generation process was conducted. The idea is to make a comparison between different models of energy systems and to show how fuel consumption...
In order to improve the efficiency and power output of combined cycle gas turbine (CCGT) power plants, a new design of combined cycle with reheat gas turbine (RGT) matched with supercritical Rankine cycle is proposed. Steam cycle is composed of supercritical single pressure level once-through with reheat Heat Recover Steam Generator (SCHRSG). Aspen plus software has been used to calculate the process...
This paper is focused on a series hybrid electric bus (SHEB). A rule-based energy management strategy is proposed by controlling the state of charge (SOC) of the battery (BT) and a variable output control for the auxiliary power unit (APU). Furthermore, a power splitter control is developed to split the power among BT and supercapacitor (SC). The optimization to obtain the values for the control levels...
In large electrical power generation systems the integrated operation of hydro and thermal power stations is considered to be more economical as compared to thermal power generation. Integrated operation results in optimum utilization of all energy sources in the most economical manner, to provide an uninterrupted supply to the consumers. Through a case study present paper aims at optimizing traditional...
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