Joint Optimization for Power Loss Reduction in Distribution Systems
TL;DR: A joint optimization algorithm of combining network reconfiguration and capacitor control is proposed for loss reduction in distribution systems and has been implemented into a software package and tested on a 119-bus distribution system with very promising results.
Abstract: In distribution systems, network reconfiguration and capacitor control, generally, are used to reduce real power losses and to improve voltage profiles. Since both capacitor control and network reconfiguration belong to the complicated combinatorial optimization problems, it is hard to combine them efficiently for better optimization results. In this paper, a joint optimization algorithm of combining network reconfiguration and capacitor control is proposed for loss reduction in distribution systems. To achieve high performance and high efficiency of the proposed algorithm, an improved adaptive genetic algorithm (IAGA) is developed to optimize capacitor switching, and a simplified branch exchange algorithm is developed to find the optimal network structure for each genetic instance at each iteration of capacitor optimization algorithm. The solution algorithm has been implemented into a software package and tested on a 119-bus distribution system with very promising results.
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TL;DR: In this article, a branch exchange method of single loop is proposed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems, and a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction.
Abstract: Network reconfiguration and capacitor placement have been widely employed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems. Reconfiguration method proposed in this paper is based on a simple branch exchange method of single loop. In this simple method of branch exchange, loops selection sequence affects the optimal configuration and the network loss. Therefore, this method has been improved by optimizing the sequence of loops selection for minimizing the energy losses in this paper. Also, a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction. For more practical application of the proposed method, different load patterns are considered and a fast method of total energy loss calculation is employed for the economic optimization of energy losses during the planning horizon. Discrete genetic algorithm (GA) is used to optimize the location and size of capacitors and the sequence of loops selection. In fact, the capacitor sizes have been considered as discrete variables. Simulated annealing (SA) is also applied to compare the performance of convergence. The proposed algorithm is effectively tested on a real life 77-bus distribution system with four different kinds of load patterns.
161 citations
Cites background or methods from "Joint Optimization for Power Loss R..."
...Therefore, the overall computing efficiency of the joint optimization algorithm is guaranteed in [10]....
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...Equation (1) has been used for determining the optimal branch exchange in a loop in [10]:...
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...Based on the ideas presented in [22] and [23], branch exchange algorithm is further simplified according to system parameter features in the capacitors optimization process in [10]....
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...Reconfiguration in each loop is performed based on the proposed simple branch exchange method in [10]....
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...Therefore, due to its high computing efficiency, the proposed method for reconfiguration in [10] has been improved in this paper by optimizing the loops selection sequence....
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TL;DR: In this article, an algorithm for reconfiguration associated with capacitor allocation to minimize energy losses on radial electrical networks considering different load levels is presented. But the proposed model is solved using a mixed integer non-linear programming approach, in which a continuous function is used to handle the discrete variables.
138 citations
Cites background or methods from "Joint Optimization for Power Loss R..."
...[15–23] consider both the capacitor allocation and the reconfiguration problems....
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...Besides, the daily load curve is not considered in [18–20,23] meaning that the system might not be in the optimal configuration for all load levels....
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...In [20], the capacitor allocation is solved by using a genetic algorithm combined with power flow analysis....
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TL;DR: A novel hybrid method of metaheuristic and heuristic algorithms is presented in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs.
Abstract: Different types of distributed generation (DG) are broadly used and optimally placed in a distribution system to improve its performance. Since the network configuration affects the system operational conditions, the network reconfiguration and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent from achieving the optimal solution. This paper presents a novel hybrid method of metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs. The developed backward/forward power flow is adopted to consider the PV(Q) model of DG. Moreover, different patterns of load types are taken into consideration to perform a practical study. To assess the capabilities of the proposed method, simulations are carried out on IEEE 33-bus and 83-bus practical distribution network of Taiwan Power Company. Furthermore, the proposed method is applied to a 33-bus unbalanced distribution network to verify its applicability in unbalanced distribution systems. The obtained results demonstrate the effectiveness of the proposed method to find optimal status of switches, as well as locations and sizes of DG units, in a rather shorter time than other approaches in the literature.
114 citations
Cites methods from "Joint Optimization for Power Loss R..."
...The loops opening consecutively based on a branch-exchange heuristic technique has been proposed in [19] to solve reconfiguration and capacitor...
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TL;DR: In this paper, the authors deal with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers.
Abstract: This paper deals with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers. The indices are developed in a way consistent with a mixed-integer linear programming (MILP) approach. A key contribution of the paper is the efficient implementation of the ${\mmb\varepsilon}$ -constraint method using lexicographic optimization in order to solve the multi-objective optimization problem. After the Pareto efficient solution set is generated, the resulting configurations are evaluated using a backward/forward sweep load-flow algorithm to verify that the solutions obtained are both non-dominated and feasible. Since the ${\mmb\varepsilon}$ -constraint method generates the Pareto front but does not incorporate decision maker (DM) preferences, a multi-attribute decision making procedure, namely, the technique for order preference by similarity to ideal solution (TOPSIS) method, is used in order to rank the obtained solutions according to the DM preferences, facilitating the final selection. The applicability of the proposed method is assessed on a classical test system and on a practical distribution system.
104 citations
Cites methods from "Joint Optimization for Power Loss R..."
...[12] presented a genetic algorithm based methodology to jointly optimize capacitor placement and least-losses reconfiguration....
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TL;DR: In this paper, the authors presented a comprehensive optimisation model that combines reactive power (VAR) optimisation and network reconfiguration to minimize power losses and eliminate voltage violations, which can be used as a basic analysis tool for active distribution networks operation schedule or planning.
Abstract: This study presents a comprehensive optimisation model that combines reactive power (VAR) optimisation and network reconfiguration to minimise power losses and eliminate voltage violations. In this model, the reactive power of distributed generators (DGs), VAR compensators, the position of tap-changer and the states of branches are formulated as continuous and discrete decision variables. The original non-convex three-phase optimisation model was converted to a mixed-integer second-order cone programming model using the second-order cone relaxation, big-M method and piecewise linearisation. The results of numerical tests showed that the proposed model can achieve significant additional gains in network loss reduction and voltage violation mitigation. This developed method can be used as a basic analysis tool for active distribution networks operation schedule or planning.
77 citations
References
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TL;DR: Accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations.
Abstract: A general formulation of the feeder reconfiguration problem for loss reduction and load balancing is given, and a novel solution method is presented. The solution uses a search over different radial configurations created by considering switchings of the branch exchange type. To guide the search, two different power flow approximation methods with varying degrees of accuracy have been developed and tested. The methods are used to calculate the new power flow in the system after a branch exchange and they make use of the power flow equations developed for radial distribution systems. Both accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations. For load balancing, a load balance index is defined and it is shown that the search and power flow estimation methods developed for power loss reduction can also be used for load balancing since the two problems are similar. >
3,985 citations
01 Apr 1994
TL;DR: An efficient approach for multimodal function optimization using genetic algorithms (GAs) and the use of adaptive probabilities of crossover and mutation to realize the twin goals of maintaining diversity in the population and sustaining the, convergence capacity of the GA are described.
Abstract: In this paper we describe an efficient approach for multimodal function optimization using genetic algorithms (GAs). We recommend the use of adaptive probabilities of crossover and mutation to realize the twin goals of maintaining diversity in the population and sustaining the, convergence capacity of the GA. In the adaptive genetic algorithm (AGA), the probabilities of crossover and mutation, p/sub c/ and p/sub m/, are varied depending on the fitness values of the solutions. High-fitness solutions are 'protected', while solutions with subaverage fitnesses are totally disrupted. By using adaptively varying p/sub c/ and p/sub ,/ we also provide a solution to the problem of deciding the optimal values of p/sub c/ and p/sub m/, i.e., p/sub c/ and p/sub m/ need not be specified at all. The AGA is compared with previous approaches for adapting operator probabilities in genetic algorithms. The Schema theorem is derived for the AGA, and the working of the AGA is analyzed. We compare the performance of the AGA with that of the standard GA (SGA) in optimizing several nontrivial multimodal functions with varying degrees of complexity. >
2,359 citations
"Joint Optimization for Power Loss R..." refers methods in this paper
...In this paper, based on adaptive genetic algorithm (AGA) presented in [22], an improved adaptive genetic algorithm (IAGA) for optimizing capacitor control is developed in this paper....
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TL;DR: In this article, the problem of capacitors placement on a radial distribution system is formulated and a solution algorithm is proposed, where the location, type, and size of the capacitors, voltage constraints, and load variations are considered.
Abstract: The problem of capacitor placement on a radial distribution system is formulated and a solution algorithm is proposed. The location, type, and size of capacitors, voltage constraints, and load variations are considered. The objective of capacitor placement is peak power and energy loss reduction, taking into account the cost of the capacitors. The problem is formulated as a mixed integer programming problem. The power flows in the system are explicitly represented, and the voltage constraints are incorporated. A solution method has been implemented that decomposes the problem into a master problem and a slave problem. The master problem is used to determine the location of the capacitors. The slave problem is used by the master problem to determine the type and size of the capacitors placed on the system. In solving the slave problem, and efficient phase I-phase II algorithm is used. >
1,832 citations
"Joint Optimization for Power Loss R..." refers background in this paper
...There are many previous works on capacitor setting/switching [1]–[8] and network reconfiguration [9]–[18], respectively, and only a few on the combination of network reconfiguration and capacitor control for the joint optimization in distribution systems....
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...Baran and Wu [1], [2] formulated the capacitor placement problem...
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TL;DR: In this paper, a nonlinear programming problem for capacitors placed on a radial distribution system is formulated and a solution algorithm is developed to find the optimal size of capacitors so that the power losses will be minimized for a given load profile while considering the cost of the capacitors.
Abstract: A capacitor sizing problem for capacitors placed on a radial distribution system is formulated as a nonlinear programming problem, and a solution algorithm is developed. The object is to find the optimal size of the capacitors so that the power losses will be minimized for a given load profile while considering the cost of the capacitors. The formulation also incorporates the AC power flow model for the system and the voltage constraints. The solution algorithm developed for the capacitor sizing problem is based on a Phase I-Phase II feasible directions approach. Novel power flow equations and a solution method, called DistFlow, for radial distribution systems are introduced. The method is computationally efficient and numerically robust, especially for distribution systems with large r/x ratio branches. DistFlow is used repeatedly as a subroutine in the optimization algorithm for the capacitor sizing problem. The test results for the algorithm indicate that the method is computationally efficient and has good convergence characteristics. >
1,391 citations
"Joint Optimization for Power Loss R..." refers background in this paper
...Baran and Wu [1], [2] formulated the capacitor placement problem...
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TL;DR: In this paper, a scheme that utilizes feeder reconfiguration as a planning and/or real-time control tool to restructure the primary feeder for loss reduction is presented.
Abstract: Feeder reconfiguration is defined as altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and tie switches. A scheme is presented that utilizes feeder reconfiguration as a planning and/or real-time control tool to restructure the primary feeder for loss reduction. The mathematical foundation of the scheme is given. The solution is illustrated on simple examples. >
1,297 citations
"Joint Optimization for Power Loss R..." refers background in this paper
...The branch exchange-type heuristic algorithm for loss minimum and load balancing reconfiguration in distribution systems is proposed in [9]–[11]....
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...There are many previous works on capacitor setting/switching [1]–[8] and network reconfiguration [9]–[18], respectively, and only a few on the combination of network reconfiguration and capacitor control for the joint optimization in distribution systems....
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