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Procedural Content Generation (PCG) can be a useful tool for aiding creativity in the process of designing game levels. Mixed-initiative level generation tools where a designer and an algorithm collaborate to iteratively generate game levels have been used for this purpose. However, it can be difficult for designers to work with tools that do not respond to the common language of games: game design...
To achieve optimal energy generation for different renewable energy resources and to control the charging and discharging functions of energy storage system by minimizing the operation cost and by satisfying the electricity demand is a seriously challenging optimization problem. The aim of the Virtual Power Producer (VPP) is to ensure the optimal scheduling of the connected units in the Islanded Smart...
This paper explores the use of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for solving multi objective optimal power flow problems. The algorithms are tested on the IEEE 30 bus system by simultaneously minimizing cost, power losses and voltage deviation under operational constraints. The Pareto optimal and fuzzy methods are employed to identify the best compromise for conflicting...
A difference hybrid genetic algorithm to solve 3-SAT problem has been developed in this paper. It is an hybrid genetic algorithm with combination of GSAT, the three-route quick sort algorithm and the cloud theory. In this algorithm, basic cloud generator is used to generate the mutation rate and cross rate. Numerical experiments have been carried out for the analytical investigation of this algorithm...
The most significant problem is to balance between generation and consumption in power systems ranging from small to large scales. This may be done by daily load scheduling in small-scale systems using metaheuristic optimization techniques such as the GA, the PSO and the SA etc. In the case of an off-grid low power wind-photovoltaic hybrid system, it is expected to power the loads without shedding...
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 considers the non-convex Economic Dispatch Problem (EDP) with power losses, prohibited operating zones, and generation cost functions modeling both valve-point loading effects and multiple fuel options. This constrained problem is stated as an unconstrained problem by using the augmented Lagrange formulation, while introducing Lagrange multipliers and penalty parameters. Then, a genetic...
In this paper, different selection, crossover including deferential evolution and mutation techniques are considered for optimizing the electrical power loss in real hydrocarbon industrial plant using genetic algorithm (GA). The subject plant electrical system consists of 275 buses, two gas turbine generators, two steam turbine generators, large synchronous motors, and other rotational and static...
This paper proposes a new method for automation and optimization of coverage-driven verification (CDV) of hardware systems that is based on evolutionary computing. In comparison with the standard CDV that utilizes random search, using this method, the convergence to the maximum coverage is much faster, fewer input stimuli are used and no manual effort is required from the user. Moreover, the optimization...
To estimate performance of computer science algorithms reliably, one has to create worst-case execution time tests. For certain algorithms this task can be difficult. To reduce the amount of human effort, authors attempt using search-based optimization techniques, such as genetic algorithms.
As wind turbines increase their power rating, the size and mass grows as well. The higher reliability is demanded in order to minimize the maintenance. Permanent magnet direct drive (PMDD) synchronous generators are a good solution since they omit the gearbox. While the large generator mass has been also a key difficult problem limiting the practical use of PMDD generator, which makes them difficult...
Online bin packing requires immediate decisions to be made for placing an incoming item one at a time into bins of fixed capacity without causing any overflow. The goal is to maximise the average bin fullness after placement of a long stream of items. A recent work describes an approach for solving this problem based on a ‘policy matrix’ representation in which each decision option is independently...
In this paper, we study parallel genetic algorithm for solving a well-known NP-hard problem in graph theory that is minimum dominating set problem. We have, at first, investigated for a high performance parallel genetic algorithm for such problem. The experiment proves that the single distributed population parallel genetic algorithm is a desired solution. Secondly, we have investigated how difficult...
In the deregulated power system congestion management is one of the most challenging tasks of System Operator. Due to congestion in the transmission lines, it is not always possible to deliver all of the contracted power transactions, where in both the buyers and sellers try to buy and sell electric power so as to maximize their profit. System Operators try to manage congestion, which otherwise increases...
Achieving a balance between the exploration and exploitation capabilities of genetic algorithms is a key factor for their success in solving complicated search problems. Incorporating a local search method within a genetic algorithm can enhance the exploitation of local knowledge but it risks decelerating the schema building process. This paper defines some features of a local search method that might...
Reactive power optimization has an important role to play in operation of power system. Optimum scheduling of reactive power reduces system losses. In this paper reactive power optimization function is taken with the objective to minimize active power losses in transmission network. This objective function is subjected to power system inequality constraints and equality constraints of active and reactive...
Genetic Algorithms represent a technique of Artificial Intelligence which has developed from the paradigm of biological evolution. They use a population of potential solutions which gradually evolve toward the best solution which satisfies an objective function. By their nature, Genetic Algorithms use random numbers. In a typical algorithm running, a random number generator is used in many occasions,...
A methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system with battery storage is addressed in this article. The aim is to find the optimal number of units guaranteeing that the life time round total system cost/emission is minimized subject to the constraint that the load energy necessities are completely covered. The system is optimized using genetic algorithms and...
The power transmission capability available from a transmission line design is limited by technological and economical constraints. Therefore, in order to maximize the amount of real power, reactive power flows must be minimized. Consequently, sufficient reactive power should be provided locally in the system to keep the bus voltages within nominal ranges in order to satisfy customer's equipments...
Wind generation is the most increasing resource in the renewable energy. Now a days, the wind power has a large installed output power capacity in the world among the renewable energy sources. The wind power integration into power system grids has some effect on power system issues as transmission congestion, optimum power flow, system stability, power quality, system economics and load dispatch....
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