Wind Integrated Thermal Unit Commitment Solution Using Grey Wolf Optimizer

The augment of ecological shield and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating renewable energy sources into existing power system. Wind power is becoming worldwide a significant component of the power generation portfolio. Profuse literature have been reported for the thermal Unit Commitment (UC) solution. In this work, the UC problem has been formulated by integrating wind power generators along with thermal power system. The Wind Generator Integrated UC (WGIUC) problem is more complex in nature, that necessitates a promising optimization tool. Hence, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm has been chosen as the main optimization tool and real coded scheme has been incorporated to handle the operational constraints. The standard test systems are used to validate the potential of the GWO algorithm. Moreover, the ramp rate limits are also included in the mathematical WGIUC formulation. The simulation results prove that the intended algorithm has the capability of obtaining economical resolutions with good solution quality

Energy commitment: a planning of energy carrier based on energy сonsumption

Purpose. Energy consumption is one of the criteria for determining the quality of life in a country. Continued supply of energy and the possibility of long-term access to resources require a comprehensive plan. One of the key issues in the field of energy planning is energy carriers. Inthis paper, a new theory is introduced to energy network studies for planning of energy carriers called Energy Commitment. In this theory, an appropriate planning is applied for energy carriers based the final energy consumption. Energy carriers are available either naturally or after the energy conversion process. Energy commitment is modeled on an energy network with the presence of electrical energy, gas energy, transportation section, agriculture section, industrial section, residential section, commercial section, and general section.Цель. Потребление энергии является одним из критериев определения качества жизни в стране. Непрерывные поставки энергии и возможность долгосрочного доступа к ресурсам требуют комплексного плана. Одним из ключевых вопросов в области энергетического планирования являются энергоносители. В данной статье в исследования энергетических сетей для планирования энергоносителей вводится новая теория под названием Energy Commitment («энергетическое обязательство»). В этой теории для энергоносителей применяется соответствующее планирование на основе конечного потребления энергии. Энергоносители доступны либо естественным путем, либо после процесса преобразования энергии. Energy Commitment моделируется в энергетической сети с учетом электрической энергии, энергии газа, транспортной отрасли народного хозяйства, сельскохозяйственной отрасли, промышленного сектора экономики, жилищно коммунального хозяйства, реального сектора экономики и прочих видов экономической активности

A Brief Analysis of Gravitational Search Algorithm (GSA) Publication from 2009 to May 2013

Gravitational Search Algorithm was introduced in year 2009. Since its introduction, the academic community shows a great interest on this algorith. This can be seen by the high number of publications with a short span of time. This paper analyses the publication trend of Gravitational Search Algorithm since its introduction until May 2013. The objective of this paper is to give exposure to reader the publication trend in the area of Gravitational Search Algorithm

A binary symmetric based hybrid meta-heuristic method for solving mixed integer unit commitment problem integrating with significant plug-in electric vehicles

Conventional unit commitment is a mixed integer optimization problem and has long been a key issue for power system operators. The complexity of this problem has increased in recent years given the emergence of new participants such as large penetration of plug-in electric vehicles. In this paper, a new model is established for simultaneously considering the day-ahead hourly based power system scheduling and a significant number of plug-in electric vehicles charging and discharging behaviours. For solving the problem, a novel hybrid mixed coding meta-heuristic algorithm is proposed, where V-shape symmetric transfer functions based binary particle swarm optimization are employed. The impact of transfer functions utilised in binary optimization on solving unit commitment and plug-in electric vehicle integration are investigated in a 10 unit power system with 50,000 plug-in electric vehicles. In addition, two unidirectional modes including grid to vehicle and vehicle to grid, as well as a bi-directional mode combining plug-in electric vehicle charging and discharging are comparatively examined. The numerical results show that the novel symmetric transfer function based optimization algorithm demonstrates competitive performance in reducing the fossil fuel cost and increasing the scheduling flexibility of plug-in electric vehicles in three intelligent scheduling modes

Applications of gravitational search algorithm in engineering

Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In a recent article the authors reviewed the principles of GSA. This article presents a review of applications of GSA in engineering including combinatorial optimization problems, economic load dispatch problem, economic and emission dispatch problem, optimal power flow problem, optimal reactive power dispatch problem, energy management system problem, clustering and classification problem, feature subset selection problem, parameter identification, training neural networks, traveling salesman problem, filter design and communication systems, unit commitment problem and multiobjective optimization problems

Solution of the Multi-objective Economic and Emission Load Dispatch Problem Using Adaptive Real Quantum Inspired Evolutionary Algorithm

Economic load dispatch is a complex and significant problem in power generation. The inclusion of emission with economic operation makes it a Multi-objective economic emission load dispatch (MOEELD) problem. So it is a tough task to resolve a constrained MOEELD problem with antagonistic multiple objectives of emission and cost. Evolutionary Algorithms (EA) have been widely used for solving such complex multi-objective problems. However, the performance of EAs on such problems is dependent on the choice of the operators and their parameters, which becomes a complex issue to solve in itself. The present work is carried out to solve a Multi-objective economic emission load dispatch problem using a Multi-objective adaptive real coded quantum-inspired evolutionary algorithm (MO-ARQIEA) with gratifying all the constraints of unit and system. A repair-based constraint handling and adaptive quantum crossover operator (ACO) are used to satisfy the constraints and preserve the diversity of the suggested approach. The suggested approach is evaluated on the IEEE 30-Bus system consisting of six generating units. These results obtained for different test cases are compared with other reputed and well-known techniques

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field

ENERGY COMMITMENT: A PLANNING OF ENERGY CARRIER BASED ON ENERGY CONSUMPTION

Purpose. Energy consumption is one of the criteria for determining the quality of life in a country. Continued supply of energy and the possibility of long-term access to resources require a comprehensive plan. One of the key issues in the field of energy planning is energy carriers. In this paper, a new theory is introduced to energy network studies for planning of energy carriers called Energy Commitment. In this theory, an appropriate planning is applied for energy carriers based the final energy consumption. Energy carriers are available either naturally or after the energy conversion process. Energy commitment is modeled on an energy network with the presence of electrical energy, gas energy, transportation section, agriculture section, industrial section, residential section, commercial section, and general section. Цель. Потребление энергии является одним из критериев определения качества жизни в стране. Непрерывные поставки энергии и возможность долгосрочного доступа к ресурсам требуют комплексного плана. Одним из ключевых вопросов в области энергетического планирования являются энергоносители. В данной статье в исследования энергетических сетей для планирования энергоносителей вводится новая теория под названием Energy Commitment («энергетическое обязательство»). В этой теории для энергоносителей применяется соответствующее планирование на основе конечного потребления энергии. Энергоносители доступны либо естественным путем, либо после процесса преобразования энергии. Energy Commitment моделируется в энергетической сети с учетом электрической энергии, энергии газа, транспортной отрасли народного хозяйства, сельскохозяйственной отрасли, промышленного сектора экономики, жилищно-коммунального хозяйства, реального сектора экономики и прочих видов экономической активности.