جستجوی مقالات مرتبط با کلیدواژه "optimal placement" در نشریات گروه "برق"

Charging stations are one of the most important pieces of equipment for electric vehicles (EV). One of the most important challenges of charging stations is their optimal location, which practically puts the operation of the system components in the maximum area. Distribution networks are the final link in the electricity supply chain for consumers. Therefore, the economic and technical efficiency of these networks guarantees a stable and secure future in the electricity industry. In this regard, it is very important to study the role of EVstations. This paper investigates, the optimal location of charging and discharging stations and the optimal operation planning of Evs in a distribution network. The effective factors in choosing the location and the optimal charging and discharging rate in the stations are a combination of technical and economic issues. Regarding technical issues, the minimization of losses, the minimization of voltage drop in feeders and the uniformity of the network load curve were considered. In the economic field, the stations were located and the charging and discharging rates were determined in such a way that the charge and discharge costs in the stations and the total cost paid for the purchase of power were minimized as much as possible. In order To manage the load on the consumer side and to unify the load curve, the price-based demand response program was considered and implemented in the simulations.To find the optimal working point, genetic metaheuristic algorithms, genetic combination-particle swarm and genetic combination-colonial competition were used. All simulations were performed in MATLAB software To evaluate the proposed methods, validation was performed in each part on the IEEE standard testing system with a bus number of 69.

Phasor measurement units (PMU) have an important role for reliable operation in the power systems. Because of the high cost of PMU and also the lack of suitable communication infrastructure to transfer the measured information, the problem of optimal PMU placement (OPP) for incomplete observability has been proposed. In this paper, a new formulation was proposed to optimize the OPP problem considering the limited number of PMU in the power system. In the proposed formulation, to achieve the higher degrees of precision in state estimation, the fitness function was defined to maximize the number of observable buses and to minimize the depth of unobservability, simultaneously. Also, a comprehensive formulation of the OPP problem was introduced to have a minimum depth of unobservability and three different scenarios were designed to study the effect of considering the depth of unobservability. To simulate the results, IEEE 14, 24, 30, 39, and 57 bus test systems were used. The calculated results showed that the proposed formulation has a proper performance e.g. in IEEE 39 bus test system which had 27 observable bus in the best solution with a maximum depth of degree as 7, could reach to the 26 observable bus with a maximum depth of degree as 4 by changing the PMU placement.

Gas fueled power stations are considerably effective in power system operation during peak hours due to their high up and down ramping rates. By increasingly penetration of gas fueled power stations in power systems and development of new technologies such as power-to-gas (ptg) units, coordinated scheduling of both electricity and natural gas (NG) networks has attracted researchers’ attention of both systems. The NG volume generated by ptg units are stored in storages to directly supply the NG demands, or to sell in NG markets. If necessary, the stored NG volumes are converted into electricity, again; this method is a suitable replacement for batteries and storages in electricity network in long-term. In this paper, a mixed integer linear programming (MILP) model is proposed for coordinated scheduling of electricity and NG networks considering ptg units. A test network integrating modified 24-bus IEEE electricity network and Belgium gas network including nine power stations (three of them are gas fueled), three vehicle to grid (v2g) stations, and three ptg stations is studied to evaluate the effectiveness of the proposed model. Results of simulations demonstrate the effectiveness of ptg units in handling the uncertainties of v2g stations charging and discharging.

Optimal placement and sizing of equipment in engineering systems is one of the most important and challenging practical problems. Installation of capacitors and distributed generations (DGs) in distribution systems has many benefits, such as improving the reliability as well as reducing the power loss, however, includes high investment costs. Hence, the maximum use of these benefits highly depends on choosing suitable locations for installation. In this paper, the Success Rate Group Search Algorithm (SRGSO) is used for optimal placement and sizing of DG sources and capacitor banks simultaneously in distributed systems. The used objective function includes costs of Expected interruption (ECOST), Energy Not Supplied (ENS), active power losses and DG and capacitor investment, operation and maintenance. To evaluate the effectiveness of the proposed algorithm in finding the optimal solution, various capacitor and DG placement scenarios are simulated on the IEEE 33-bus radial distribution test system. The simulation results show that the proposed method is more effective and has higher capability for solving the problem of capacitor and DG placement, compared to previously proposed methods. Using the proposed method in this paper, the value of active power losses as well as bus voltage profile are improved more than other investigated methods.

Power switches are among the equipment that can help improve the distribution system condition and reduce the cost of failure at times of error. Finding the optimal location and number of these switches in the distribution system can be modeled with a variety of objective functions as a nonlinear optimization problem to improve reliability, reduce energy not supplied and other system costs. In this paper, a Hybrid Particle Swarm Optimization with Sinusoidal and Cosine Acceleration Coefficients (H-PSO-SCAC) is used to solve the problem of optimal placement of switches with the goal of reducing the cost of switches installation and outage simultaneously in a software format for the use of Malayer Distribution Company operators and other sections. The simulation results have been tested using the corresponding algorithm on the Malayer 108-bus distribution feeder and IEEE 118-bus sampling network and compared with the results of other methods. The results show that the algorithm (H-PSO-SCAC) is better than other algorithms in terms of response quality and computational efficiency, also its implementation in a user friendly software has made it easy for operators and Users to use.

One of the most critical and complex issues in long-term planning of distribution networks is the optimal placement of distribution transformers. In this paper, the optimal placement of distribution transformers was investigated based on a complete and multi-objective function. In the proposed method, location, optimal capacity, and the service area are determined by minimizing costs (investment, operation, reliability) and improving reliability and power quality parameters (voltage drop) due to electric restrictions (radial structure, voltage drop and equipment capacities). The planning of distribution networks is complicated due to the existence of numerous and multiple-criteria decision-making variables in objective functions; hence in this paper, the symbiotic organisms search (SOS) algorithm was used as a new heuristic optimization algorithm to solve the problem of long-term planning of distribution networks. The proposed method is tested on a real distribution network to evaluate the performance of the proposed algorithm,  Comparing the results of the proposed algorithm with the results of studies with genetic algorithms (GA), biogeography-based optimization (BBO) and imperialist competitive algorithm (ICA), indicates the performance and advantages of the proposed algorithm over other algorithms.

in this Paper, Optimal placement and sizing of DGs is considered as an engineering optimization problem. Due to integration and influence of DGs in distributed networks, optimal location and sizing of them are done based on objective functions such as: voltage profile improvement, power loss reduction, reliability improvement, restraining the increase of power plant, etc. These goals considering the NSGA-II algorithm with cold standby strategy will be investigated and simulated on IEEE 33-bus standard test system. In order to implement the concept of Cold Standby theory, a group of DGs are considered which are off in normal condition but in fault condition, these DGs turn on and help to reconstruction the network. In order to measuring reliability, used the expected energy not supply (EENS) index. Optimization is done with two goals: reduction of EENS and the cost, including investment cost and power loss cost. Moreover, voltage profile improvement has been applied as a function penalty. Simulation has been done in MATLAB software and results show the effectiveness and capability of proposed algorithm.

Since distribution networks incorporate a large share of the losses in power systems, reducing losses in these networks is one of the most important issues of global networks, including issues that have always been taken into consideration. There are several ways to reduce losses in distribution networks, one of which is the installation of distributed generation units. Renewable sources can supply a clean and smart solution to the increased demands. Thus, Photovoltaic (PV) and Wind Turbine (WT) are taken here as resources of Distributed Generation (DG). Location and sizing of distributed generation have affected largely on the system losses. In this article, Exchange Market Optimization Algorithm (EMA) is proposed for optimal location and sizing of DG based renewable sources for the 69 buses distribution system. The exchange market algorithm on IEEE radial distribution system is simulated and studied using Matlab software and the results of the exchange market algorithm are compared with other algorithms. The results show the effectiveness of the exchange market algorithm in finding the optimal location and sizing of DG to reduce losses and improve the voltage profile.