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In this paper, we formulate the unmanned aerial vehicle path planning problem as a multi-objective mixed integer programming problem. We minimize the fuel and time consumption at the same time. The elastic constraint method for multi-objective optimization is used to solve the problem. Experiment results show the trade off information between the two objectives, and the effectiveness of our proposed...
Optimal power flow (OPF) and security-constrained OPF (SCOPF) studies are important tools for both planning and operation of power supply systems. Conventional gradient-based SCOPF methods are commonly used for that purpose, but when analysed system is overstressed with severe multiple contingencies, conventional SCOPF methods may fail to converge. In such cases, meta-heuristic SCOPF methods can be...
In this paper, we evaluate a multi-objective-moving-horizon-optimization (MO-MHO) approach as an instrument for improvement of economic dispatch in microgrids. In particular, we investigate the effect of adaptation of the multi-objective optimization strategy used in the moving horizon framework on the end result of the economic dispatch. Power dispatch in microgrids is inherently a high-dimensional...
We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear...
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...
Optimal power flow is the highly constrained, nonlinear and non-convex optimization problem of power system. This present paper proposed metaheuristic Passing Vehicle Search algorithm for the solution of different Optimal Power flow problems. Proposed approach examined on IEEE 30 bus test system for different objective function like fuel cost, active and reactive power losses. The proposed PVS algorithm...
The Economic Load Dispatch problem is an optimization problem which minimizes cost such that the load demand is met and the generating equality and inequality constraints are satisfied. Previously, conventional techniques like linear programming and lambda iteration were applied to solve the economic dispatch problem given their simplicity. Nevertheless, they do not always converge to global optimum...
Optimal power flow is highly constrained, non linear and non convex optimization problems of the power system. This present paper introduced meta heuristic Grey Wolf Optimizer (GWO) algorithm to solve of OPF problems equipped with shunt connected Flexible AC transmission (FACTS) device called Static Synchronous Compensator (STATCOM). Different objective functions Fuel Cost and Voltage Deviation are...
Optimal power flow is the highly constrained, nonlinear and non-convex optimization problem of power system. This present paper proposed metaheuristic Grey Wolf Optimization algorithm for the solution of different Optimal Power flow problems. Proposed approach examined on IEEE 30 bus test system for different objective functions like Fuel Cost, Voltage Deviation and Voltage Stability Enhancement....
Optimal power flow is highly constrained, non linear and non optimization problems of the power system. This present paper introduced meta heuristic Grey Wolf Optimizer (GWO) algorithm to solve of OPF problems equipped with shunt connected Flexible AC transmission (FACT) device called Static VAR Compensator( SVC). Total three objective functions Fuel Cost, Voltage Deviation and Active power loss are...
Vehicle navigation now a day, it has used the navigation devices for guided the user to get the destination point. The requirement of the user in general must be arrived by the right destination. In usual work of navigation system, it directed the path with shortest path, by did not calculate the time consuming as the traffic condition. Which effect to fuel consumption of the vehicle. The vehicle...
This paper is about economic dispatch with PV generation including transmission losses considering emission as constraint using particle swarm optimization. This objective consider the minimization of fuel cost with emissions constrained of thermal generating units with scheduling for sharing of different photo-voltaic generating units to fulfill the load demand in such a way to minimize the total...
This paper presents a new power system planning strategy by combining Whale Optimization Algorithm (WOA) with pattern search algorithm (PS). The proposed approach has been carried out on the IEEE 30-bus test system considering several objective functions, such as generating fuel cost, voltage profile improvement, minimization of total power losses and emission reduction are also considered. The obtained...
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...
Day to day growing demand of electric energy, insufficiency of energy generation resources and increasing thermal power generation cost necessitates economic thermal power generation scheduling. Emission pollutants are required to be reduced as stringent regulations has been enforced to protect environment. In this article, interactive fuzzy technique is applied to solve the real and reactive power...
The main objective of this paper is to develop an Eco-Traffic Signal System (Eco-TSS) that can improve fuel consumption and delays at an isolated intersection under Connected Vehicle environment. The proposed system consists of an eco-driving algorithm and a traffic signal optimization process to find an optimal solution minimizing fuel consumption and delays. We designed a bi-level optimization method...
Since maritime transportation is the most cost-efficient way to transport goods, it has experienced a significant growth in the last few decades due to global trade and economic development. Consequently, CO2 emissions accounting for this sector have also risen. The purpose of this paper is to estimate and minimize the amount of CO2 emissions generated while a vessel is in the hoteling phase, both...
This paper proposes a distribution optimal power flow (D-OPF) model for the operation of microgrids. The proposed model minimizes not only the operating cost, including fuel cost, purchasing cost and demand charge, but also several performance indices, including voltage deviation, network power loss and power factor. It co-optimizes the real and reactive power form distributed generators (DGs) and...
Optimization, the best way of doing things, is obviously of great interest in the practical world of engineering. In recent years, for power system management, many important decisions are made by describing the system under study as precisely and quantitatively as possible, selecting some measures of system effectiveness, and then seeking the state of the system which gives the most desirable solution...
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,...
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