A. Augugliaro

Voltage regulation and power losses minimization in automated distribution networks by an evolutionary multiobjective approach

In this paper, the problem of voltage regulation and power losses minimization for automated distribution systems is dealt with. The classical formulation of the problem of optimal control of shunt capacitor banks and Under Load Tap Changers located at HV/MV substations has been coupled with the optimal control of tie-switches and capacitor banks on the feeders of a large radially operated meshed distribution system with the aim of attaining minimum power losses and the flattening of the voltage profile. The considered formulation requires the optimization of two different objectives; therefore the use of adequate multiobjective heuristic optimization methods is needed. The heuristic strategy used for the optimization is based on fuzzy sets theory. After a brief description of the general problem of optimal control of voltage and power losses in automated distribution networks, the most recent papers on the topic are reported and commented. Then the problem formulation and the solution algorithm are described in detail. Finally, numerical results on a large distribution system demonstrate that the proposed formulation and approach are effective and feasible for finding an optimal generalized dispatching schedule.

Minimum losses reconfiguration of MV distribution networks through local control of tie-switches

This paper deals with the problem of optimal reconfiguration of radial distribution networks for minimum loss operation. The proposed control strategy of the open-closed status of the tie switches is distributed, since every MV/LV node is provided with local controllers having some measured entities as input. It also does not prevent the system from the future implementation of centralized control; instead, it may represent the first step towards a complete automation of the distribution system. The proposed strategy is organized in hierarchic levels, the highest of which may be in the future a central control. After introducing the general problem of network reconfiguration, a review of the state of art on the subject is reported, even though the solution methodologies are usually related to the centralized formulation of the reconfiguration problem. The proposed local control strategy is outlined, and a detailed description of its different parts is reported with special attention to all the measures for a better performance of the system. Results of a number of simulation runs are reported in order to test the behavior of the proposed local control system in different possible operating conditions.

Multiobjective service restoration in distribution networks using an evolutionary approach and fuzzy sets

Abstract In this article, the service restoration (SR) problem in electrical distribution networks is dealt with using an evolutionary strategy (ES) with a fuzzy definition of the conflicting objectives. The normal operation status allows the remote control of tie-switches, of capacitor banks and load connection. When a permanent fault occurs, the same remote control actions can be performed with the aim of restoring the service in the concerned areas. The status of these remotely controllable elements is the boolean optimisation variables for the SR problem. Besides this, here the SR problem is dealt with in a multiple objectives (MO) formulation. Indeed, the power losses’ term is considered as a further objective to be minimised, together with the primary objective of maximising the number of supplied loads. Generally, the MO formulation of an optimisation problem requires a unique expression for the global objective function. In this particular case, the used ES approach necessarily requires the definition of a ‘global performance’ index, which is derived on the basis of the fuzzy sets theory, outperforming the weighed sum formulation of the same problem. After a brief discussion on the SR problem and a short review of the state-of-art on the topic, the proposed ES and the fuzzy MO formulation of the SR problem is presented in detail. Results obtained using this procedure applied to a test system are presented and discussed.

Service restoration in compensated distribution networks using a hybrid genetic algorithm

In this paper a genetic algorithm (GA) based approach to the service restoration (SR) problem in automated distribution networks is presented. Normal operation within the network comprises both automatic reconfiguration and compensation so as to reduce power losses, allow load balancing and improve the voltage profile. In the restorative state, the reconfiguration is performed together with compensation, taking mainly into account the load supply requirement and secondarily, the losses reduction requirement. After a general discussion on the restoration problem together with a short review of recent papers on the topic, a solution strategy is proposed. Then, a short account about classical GA searching mechanism is reported in order to emphasize the difficulties arising from the application of a classical GA to the restoration problem. Therefore, the hybridization strategy of the GA is presented in depth, with particular regard to the description of some new operators, of the objective function and of the constraints expression. Finally, test results and concluding remarks are reported.

Evolving non-dominated solutions in multiobjective service restoration for automated distribution networks

Abstract The problem here dealt with is that of Service Restoration (SR) in automated distribution networks. In such networks, configuration and compensation level as well as loads insertion status can be remotely controlled. The considered SR problem should be handled using Multiobjective Optimization, MO, techniques since its solution requires a compromise between different criteria. In the adopted formulation, these criteria are the supply of the highest number of loads and the minimum power losses. The Authors propose a new MO approach, the Non-dominated Sorting Fuzzy Evolution Strategy, NS_FES, which uses part of the Non-dominated Sorting Genetic Algorithm, NSGA, proposed by K. Deb. The ability of NSGA to divide a population of solutions in classes of dominance allows a fruitful application of another efficient MO strategy already proposed and tested by the Authors (FES, Fuzzy Evolution Strategy). In this way, diversity and high quality of solutions is possible. After a brief description of the SR problem and a review of the approaches recently proposed in literature, the NS_FES solution strategy is presented in detail. Finally, test results using the three approaches (NSGA, FES, NS_FES) are carried out and compared.

Optimal capacitive compensation on radial distribution systems using nonlinear programming

Abstract A mathematical model for optimal capacitive compensation on radial distribution systems with both switched and fixed capacitors is illustrated in this paper. The objective is the optimization of the number, size, location and switching-on time of the capacitors in order to minimize the cost of both power and energy losses and of compensation equipment. The model includes constraints on voltage rise at system nodes. As the objective function and the constraints are nonlinear a nonlinear programming package has been used for the optimization of the model. An example of its application is reported.

An efficient iterative method for load-flow solution in radial distribution networks

In this paper, an efficient method for radial distribution networks solution is proposed. The efficiency of the presented strategy makes it suitable for distribution automation applications. The method is based on an iterative algorithm with some special procedures to increase the convergence speed; the bus voltages are considered as state variables according to approaches that are common in literature. After the presentation of the general problem and of the state of the art on the subject, the proposed methodology is treated in detail. It uses a simple matrix representation for the network topology and branch current flows management. The method has been applied to some test systems already used in literature so as to put into evidence its properties mostly in terms of calculation times reduction. The obtained results confirm that it outperforms other solution methods for radial networks.

An efficient greedy approach for minimum loss reconfiguration of distribution networks

Abstract This paper proposes a two-stage heuristic procedure, based on a greedy approach, for the minimum loss reconfiguration of MV distribution networks. The first stage of the procedure is based on a minimum flow rule and consists in the progressive opening of all switchgears which are initially assumed closed, in order to convert the meshed network into a completely radial network. From the radial network thus created, one then proceeds to search for further improvements minimizing the losses, applying a single branch exchange technique, which in turn is composed of two procedures: one is based again on the minimum flow rule whereas the other is based on a load transfer derived from that proposed by Civanlar et al. The entire procedure has been implemented in a software package which has been used to assess its efficiency. To this end, all examples of the application of the various methods found in the existing literature for which data were available have been reconsidered. The analysis of the results of this comparison has demonstrated the efficiency of the proposed procedure which at no time produced configurations with losses greater than those of the corresponding configurations arrived at with other methodologies.

An Evolutionary Parallel Tabu Search approach for distribution systems reinforcement planning

Abstract In this paper a new meta-heuristic optimisation technique is proposed. The method is based on the Parallel Tabu Search (PTS) algorithm and the application is the optimal electrical distribution systems reinforcement planning through the installation of photovoltaic plants, parallel cables, capacitor banks and transformers. The issue is a combinatorial optimisation problem; the objective function is a non-linear expression of a large number of variables. In these cases, meta-heuristics have proved to work well and one of the most efficient is the Tabu Search algorithm. For large-scale problems, parallelisation improves Tabu Search computational efficiency as well as its exploration ability. In this paper, an enhanced version of PTS, Evolutionary Parallel Tabu Search (EPTS), is proposed. It performs reproduction operators on sub-neighbourhoods directing the search towards more promising areas of the search space. The problem of distribution systems reinforcement planning has been studied in detail and the results of the application show that the EPTS outperforms the PTS and Particle Swarm Optimisation algorithms. The algorithms performance is also tested on mathematical test functions and other properties of the proposed algorithm are examined.

Voltage collapse proximity indicators for radial distribution networks

Based on the single-line equivalent system of a radial distribution network, two simple methods to evaluate two efficient voltage collapse proximity indicators are presented and discussed. The two methods differ on the determination of the parameters which define the equivalent system from which the indicators are derived. Both methods can be conveniently used jointly for on-line applications to assess the state of a distribution system from the viewpoint of voltage stability; the first to monitoring the stability margin of the whole system loading, the second to sharpen the stability analysis at the critical node when the system operating point is in the vicinity of the Readability limit. The effectiveness of the proposed methods is tested on a 11 kV radial distribution system of 85 nodes and results are compared with those found by a repetitive load flow calculation.