M. Hajibeigy; V. Talavat; S. Galvani
Abstract
Due to ever-increasing energy requirements, modern distribution systems are integrated with renewable energy sources (RESs), such as wind turbines and photovoltaics. They also bring economic, environmental, and technical advantages. However, they face the network operator with decision-making challenges ...
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Due to ever-increasing energy requirements, modern distribution systems are integrated with renewable energy sources (RESs), such as wind turbines and photovoltaics. They also bring economic, environmental, and technical advantages. However, they face the network operator with decision-making challenges due to their uncertain nature. Modern distribution systems usually operate at safety margins, and any contingency may lead to power supply losses. In this regard, any attempts to increase the planner/operator's awareness of the network situation will help improve the decision quality. This paper determines the optimal locations of the RESs to enhance the expected power not served as a reliability index. Besides, it reduces power losses and minimizes the 95\% confidence interval of power losses, as much as possible for having more awareness of network states. The K-medoids data clustering method is applied to handle the uncertainties of the RESs and demand loads. The MOPSO, NSGA II, and MOGWO algorithms are used to solve the proposed problem. The efficiency of the proposed approach is tested on the IEEE standard 33-bus and 118-bus distribution networks. The obtained results show that it is possible to reach a better confidence interval while keeping the losses and reliability index at a desired level. Considering solutions with identical losses and reliability index, the confidence interval of power losses using the MOPSO algorithm is 6.86% and 39.82% better rather than the NSGA II and MOGWO algorithms in the 33-bus distribution network and it is 30.23% and 129.63% better in the 118-bus distribution network.
J. Salehi; F.S. Gazijahani; A. Safari
Abstract
Executing interruptible loads (ILs) can be significantly effective for optimal and secure operation of power systems. These ILs can aid the operators not only to increase the reliability of the power supply but also to reduce the procurement costs of the whole system. Therefore, determining the optimal ...
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Executing interruptible loads (ILs) can be significantly effective for optimal and secure operation of power systems. These ILs can aid the operators not only to increase the reliability of the power supply but also to reduce the procurement costs of the whole system. Therefore, determining the optimal location and capacity of ILs for a given incentive rate is of great interest to distribution companies. To do so, in this paper simultaneous allocation and sizing of ILs, wind turbines (WT), photovoltaic (PV) and capacitors have been done in the radial distribution network for different demand levels and subsequently the optimal value of compensation price for the ILs has been determined. Given the probabilistic nature of load, wind and solar generation as well as the price of energy at the pool, we have also proposed a stochastic model based on fuzzy decision making for modelling the technical constraints of the problem under uncertainty. The objective functions are technical constraint dissatisfaction, the total operating costs of the Distribution Company and CO2 emissions which are minimized by NSGA2. To model the uncertainties, a scenario-based method is used and then by using a scenario reduction method the number of scenarios is reduced to a certain number. The performance of the proposed method is assessed on the IEEE 33-node test feeder to verify the applicability and effectiveness of the method.
Distribution Systems
H. Yousefi; S.A. Gholamian; A. Zakariazadeh
Abstract
In this paper, a distributed method for reactive power management in a distribution system has been presented. The proposed method focuses on the voltage rise where the distribution systems are equipped with a considerable number of photovoltaic units. This paper proposes the alternating direction method ...
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In this paper, a distributed method for reactive power management in a distribution system has been presented. The proposed method focuses on the voltage rise where the distribution systems are equipped with a considerable number of photovoltaic units. This paper proposes the alternating direction method of multipliers (ADMMs) approach for solving the optimal voltage control problem in a distributed manner in a distribution system with high penetration of PVs. Also, the proposed method uses a clustering approach to divide the network into partitions based on the coupling degrees among different nodes. The optimal reactive power control strategy is conducted in each partition and integrated using ADMM. The proposed method is tested on a 33 bus IEEE distribution test system and a modified IEEE 123-node system. The result evidence that the proposed method has used the lower reactive power if compared to the conventional method.
Distribution Systems
A. Lashkar Ara; H. Bagheri Tolabi; R. hosseini
Volume 4, Issue 2 , December 2016, , Pages 93-103
Abstract
In this paper, a combination of simulated annealing (SA) and intelligent water drops (IWD) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (WT) as a distributed generation (DG) and dynamic voltage restorer ...
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In this paper, a combination of simulated annealing (SA) and intelligent water drops (IWD) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (WT) as a distributed generation (DG) and dynamic voltage restorer (DVR) as a distributed flexible AC transmission systems (DFACT) unit in a distribution system. The objectives of this research are to minimize active power loss, minimize operational cost, improve voltage stability, and increase the load balancing of the system. For evaluation purposes, the proposed algorithm is evaluated using the Tai-Power 11.4-kV real distribution network. The impacts of the optimal placement of the WT, DVR, and WT with DVR units are separately evaluated. The results are compared in terms of statistical indicators. By comparing all the testing scenarios, it is observed that the multi-objective optimization evolutionary algorithm is more beneficial than its single-objective optimization counterpart. Also, the obtained results show that the proposed SAIWD method outperforms the IWD method and other intelligent search algorithms such as genetic algorithm or particle swarm optimization.
H. Bagheri Tolabi; M. H. Ali; M. Rizwan
Volume 2, Issue 2 , December 2014, , Pages 91-102
Abstract
This paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-Distributed Generation (DG). The purposes of this research are mitigation of losses, improving the voltage profile and equalizing ...
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This paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-Distributed Generation (DG). The purposes of this research are mitigation of losses, improving the voltage profile and equalizing the feeder load balancing in distribution systems. To reduce the search space, the improved analytical method has been employed to select the optimum candidate locations for multiple-DGs, and the intelligent water drops approach as a novel swarm intelligence based algorithm is used to simultaneously reconfigure and identify the optimal capacity for installation of DG units in the distribution network. In order to facilitate the algorithm for multi-objective search ability, the optimization problem is formulated for minimizing fuzzy performance indices. The proposed method is validated using the Tai-Power 11.4-kV distribution system as a real distribution network. The obtained results proved that this combined technique is more accurate and has the lowest fitness value as compared with other intelligent search algorithms. Also, the obtained results leadto the conclusion that multi-objective simultaneous placement of DGs along with reconfiguration can be more beneficial than separate single-objective optimization.
M. Allahnoori; Sh. Kazemi; H. Abdi; R. Keyhani
Volume 2, Issue 2 , December 2014, , Pages 113-120
Abstract
The microgrid concept provides attractive solutions for reliability enhancement of power distribution systems. Normally, microgrids contain renewable-energy-based Distributed Generation (DG) units, which their output power varies with different environmental conditions. In addition, load demand usually ...
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The microgrid concept provides attractive solutions for reliability enhancement of power distribution systems. Normally, microgrids contain renewable-energy-based Distributed Generation (DG) units, which their output power varies with different environmental conditions. In addition, load demand usually changes with factors such as hourly and seasonal customer activities. Hence, these issues have to be considered in evaluating the reliability of such a power distribution system. This paper evaluates the reliability performance of distribution systems with considering uncertainties in both generation and load demands. The results of applying the proposed approach on a case study system verify its advantages compared to the previous studies.
J. Moshtagh; S. Ghasemi
Volume 1, Issue 1 , June 2013, , Pages 12-21
Abstract
In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent ...
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In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method, 33-bus and 69-bus distribution networks have been employed which have led to the desired results.
T. Barforoushi; M. Rasoulpoor
Volume 2, Issue 1 , June 2007, , Pages 40-48
Abstract
Generally, the failure rate and the repair time of system components are constant parameters in reliability assessment of electric distribution systems. A failure of component is resulted from failing in the operation or overloading. In addition, there exist cases where, the repair times of components ...
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Generally, the failure rate and the repair time of system components are constant parameters in reliability assessment of electric distribution systems. A failure of component is resulted from failing in the operation or overloading. In addition, there exist cases where, the repair times of components are small and tolerable from customer point of view. Thus, tolerable repair times may be overlooked in the reliability evaluation of distribution systems. Therefore, by omitting the tolerable failures, reliability indices that are more reasonable, will be gained. In this paper, impacts of omitting customer tolerable repair time on electric distribution system reliability are studied. A simple model of circuit breaker, which differs from other components, is included. Monte Carlo simulation method is used for calculating reliability indices. A meshed distribution system is selected as a test system and simulations are performed and analyzed. Simulation results show that unavailability of load points are decreased resulting from omitting sustainable repair time, and also, it is required to include breaker model in distribution reliability evaluation.
