Seyed Erfan Hosseini; Alimorad Khajehzadeh; Mahdiyeh Eslami
Articles in Press, Accepted Manuscript, Available Online from 18 August 2021
Abstract
The generation rescheduling is one of the most important methods used in correctional congestion management, which has been the subject of many studies. In the deregulated environment, relieving congestion has a significant impact on the operation and security of the transmission system. Consequently, ...
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The generation rescheduling is one of the most important methods used in correctional congestion management, which has been the subject of many studies. In the deregulated environment, relieving congestion has a significant impact on the operation and security of the transmission system. Consequently, alleviation of transmission network congestion in all power systems is imperative. In addition, the cost is a top priority in all markets, both electrical and non-electrical. In this paper, the problem of managing congestion is solved using rescheduling (increasing or decreasing) of the active power output of the generators. However, the change in the active power generation imposes a cost depending on the prices offered by the generation companies. The objective is to reschedule the power generation of power plants in such a way as to minimize the congestion cost. The crow search optimization algorithm is employed to determine the optimal solution. Different constraints including those related to the network, transmission lines, and power plants are all modeled and considered in this study. Moreover, various contingencies related to line outage are taken into consideration to cause congestion and necessary measure are applied to relieve the congested lines with the least possible cost. In order to evaluate the accuracy and effectiveness of the proposed approach in finding the optimal solution, it is conducted on IEEE 30 and 57 bus test systems. The results obtained for the various cases studies indicate the superiority of the proposed method in comparison with other techniques presented in the literature.
Mojtaba Jamiati
Volume 10, Issue 02 , Spring 2021, , Pages 99-103
Abstract
This paper presents an optimization model for the optimal placement of hybrid system of diesel generator, wind turbines and photovoltaic. For this, the proposed objective function has been formulated based on: cost of purchasing equipment, cost of gas split, distance from electrical substation, cost ...
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This paper presents an optimization model for the optimal placement of hybrid system of diesel generator, wind turbines and photovoltaic. For this, the proposed objective function has been formulated based on: cost of purchasing equipment, cost of gas split, distance from electrical substation, cost of land acquisition, costs of water split. The calculations are done based on amount of investment for each 3 types of DGs, generating time of each, operation and maintenance costs and bank financial supports (loans). The aim of the optimization process is to design the system with a loss of load probability that is less than 1%. The problem has been optimized by Honey-bee mating optimization (HBMO) algorithm. The honey bee is a social insect that can only survive as a member of a community, or colony. Simulation has been performed on a practical test system in Iran. The results obtained of the proposed algorithm were analyzed and compared with related values of Particle Swam Optimization (PSO) algorithm and related values of genetic algorithm.
Mostafa Karimi; Mohsen Simab; Mehdi Nafar
Volume 09, Issue 02 , Spring 2020, , Pages 59-64
Abstract
The topic of distribution network reconfiguration has been recognized as a common problem in the operation of distribution networks. Up to now, reconfiguration of the distribution network has been used to reduce power loss, issues with reliability and emergency problems. As a result of the increasing ...
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The topic of distribution network reconfiguration has been recognized as a common problem in the operation of distribution networks. Up to now, reconfiguration of the distribution network has been used to reduce power loss, issues with reliability and emergency problems. As a result of the increasing installation rate of Distributed Generations (DGs) and the increasingly increasing number of Electric Vehicles (EVs), distribution network operators have faced new problems as a result of high sensitive loads. These new facets of the problem of network operation consist of the problem of congestion and enable the business mechanism to be executed by an existing distribution market. With the application of Distribution Locational Marginal Price (DLMP), using Particle Swarm Optimization (PSO), this paper introduces a new methodology to solve this problem. As a suitable case study, the standard IEEE 33-bus network has been selected and simulation results show the compatibility of the proposed system. In the case of not considering DGs and the problem of congestion, comparisons with other papers were also discussed. The participation of DGs in the electricity distribution industry, the issue of congestion and the numerical results have been shown and discussed below.
Ava Alamatsaz; Mohammad Esmaeil Nazari
Volume 08, Issue 01 , Winter 2019, , Pages 1-7
Abstract
A host of technologies has been developed to achieve these aims of the smart grid. Some of these technologies include plug-in electric vehicle, demand response program, energy storage system and renewable distributed generation. However, the integration of the smart grid technologies in the power system ...
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A host of technologies has been developed to achieve these aims of the smart grid. Some of these technologies include plug-in electric vehicle, demand response program, energy storage system and renewable distributed generation. However, the integration of the smart grid technologies in the power system operation studies such as economic emission unit commitment problem causes two major challenges. Pumped storage unit with the capability of storing energy can provide spinning reserve and consequently decrease total cost and environmental emission. The goal of this study is to develop and examine a hybrid GA-heuristic and deterministic optimization algorithm for solving the UC problem for a smart grid with considerations for pumped storage as an energy storage system. Simulation results show improvements in total cost and environmental emission by 1.27 and 4.09%, respectively.
Leila kamyabi; Saeid Esmaeili
Volume 07, Issue 04 , Autumn 2018, , Pages 169-176
Abstract
Finding minimum number of connecting lines is as important as locating power quality monitors (PQMs) for full observability of power system. Therefore, a PQM placement method should determine both optimum buses and lines, since utilities can make better decisions for monitoring of power system with this ...
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Finding minimum number of connecting lines is as important as locating power quality monitors (PQMs) for full observability of power system. Therefore, a PQM placement method should determine both optimum buses and lines, since utilities can make better decisions for monitoring of power system with this information. This paper attempted to propose a new method to locate the PQMs at various unobservability depths. In this method, the problem of placement is solved on three levels, taking into account the limited number of channels required for measuring each bus. At the first level of this method, the optimum combination of zero injection buses (ZIBs) is achieved. At the second level, different combinations of connecting lines are produced, while the third level determines the best location of monitors in different nuobservability depths. In addition, the third level identifies the critical buses and their effects on the number and location of monitors. Moreover, the best location for installing monitors and the number of channels required by equipment in each depth will be specified. The results of applying the new method on 14-bus IEEE network demonstrate the ideal performance.
M. Abedi
Volume 05, Issue 04 , Autumn 2016, , Pages 175-183
Abstract
In this paper, a novel algorithm for the load flow analysis problem in an islanded microgrid is proposed. The problem is modeled without any slack bus by considering the steady state frequency as one of the load flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an ...
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In this paper, a novel algorithm for the load flow analysis problem in an islanded microgrid is proposed. The problem is modeled without any slack bus by considering the steady state frequency as one of the load flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an islanded microgrid, a new formula for load flow equations is proposed. A hybrid optimization algorithm, named (ICGA), is developed, based on imperialist competitive algorithm (ICA) and genetic algorithm (GA) thinking, to minimize the total active and reactive power mismatch in the islanded microgrid. The performance of the proposed algorithm is compared with the GA, Newton-trust and time domain methods. The results provide support for the validity of the paper algorithm.
Naser Ghorbani; Ebrahim Babaei; Sara Laali; Payam Farhadi
Volume 05, Issue 01 , Winter 2016, , Pages 11-21
Abstract
This paper proposes per unit coding for combined economic emission load dispatch problem. In the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. In the proposed per unit coding, each function is transformed into per ...
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This paper proposes per unit coding for combined economic emission load dispatch problem. In the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. In the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. In this paper, particle swarm optimization is used for solving economic emission load dispatch problem. In order to show the advantages of the proposed method, 25 independent case studies are conducted on systems holding three and six power units with different influence percentages of each function are investigated. The obtained results are compared with those of other methods such as Biogeography Based Optimization, Tabu Search, NSGA-II and etc. The obtained results properly show the superiority of the proposed method to combine economic emission dispatch problem over the penalty factor technique and other conventional combined approaches.
Seyyed Amir Hashemi Zadeh1; Mostafa Zamani Mohi Abadi
Volume 03, Issue 01 , Winter 2014, , Pages 17-22
Abstract
Designing of a PID controller is a very common method for industrial process control and due to its very simple and efficient function; it is used in a wide variety of industrial applications. PID controller to reduce the steady state error and dynamic response of the system is used. PID controller design ...
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Designing of a PID controller is a very common method for industrial process control and due to its very simple and efficient function; it is used in a wide variety of industrial applications. PID controller to reduce the steady state error and dynamic response of the system is used. PID controller design is an inevitable problem in setting the coefficients need to try a lot of trial and error, therefore the optimization of parameters in this controller is attention of many researcher and there are many methods to find optimal parameters of PID controller. Fast and exactly adjustment of the parameters optimized controller is to create high quality answers. In this paper, an optimized tuning method for PID controller is presented. In this method the PSO algorithm is used to design the parameters of an AVR (Automatic Voltage Regulation) system using various fitness functions. Easy implementation, stable convergence characteristic and high computational efficiency are among advantages of presented method.
Setareh Shafaghi; Fardad Farokhi; Reza Sabbaghi-Nadooshan
Volume 02, Issue 1 , Winter 2013, , Pages 53-60
Abstract
Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ...
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Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optimization uses a similar mechanism to solve the optimization problem. Usually the main difficulties of evolutionary algorithm for solving the optimization problem are: early convergence, loss of population diversity, and placing in a local minimum .Therefore, it needs the way that preserves the variation and tries to avoid trapping in local minimum. In this paper by combining ant colony algorithm and mutation hybrid algorithms that leads to the better solution for optimization of FPGA (Field Programmable Gate Array) placement problem is made. They are different types of swarm intelligence algorithm. After designing the algorithm, its parameters tuning have been done by solving several problems, and then the proposed methods have been compared with the other approaches. The results show that in most problems, the proposed hybrid method is able to obtain better solutions and makes fewer errors.
K. G. Firouzjah; A Sheikholeslam
Volume 01, Issue 03 , Summer 2012, , Pages 161-173
Abstract
This paper presents a fault location technique for transmission lines with minimum current measurement. This algorithm investigates proper current ratios for fault location problem based on thevenin theory in faulty power networks and calculation of short circuit currents in each branch. These current ...
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This paper presents a fault location technique for transmission lines with minimum current measurement. This algorithm investigates proper current ratios for fault location problem based on thevenin theory in faulty power networks and calculation of short circuit currents in each branch. These current ratios are extracted regarding lowest sensitivity on thevenin impedance variations of the network structure. Proposed algorithm compares current ratios from offline calculations with corresponding values achieved from measurements with a look-up table system. Best solution based on Dynamic Time Warping (DTW) algorithm is introduced as an output (location of the fault) which includes the line and the distance. Among many current ratios to form look-up table system, the minimum number of them will be extracted by a multi-objective optimization technique using Bees Algorithm (BA). This extraction is based on lowest possible number of buses for instruments installation and required current measurements, estimation accuracy and sensitivity degree from thevenin impedances changes. Accuracy of proposed algorithm is evaluated in a widely used multi-machine network of Western Systems Coordinating Council (WSCC).
