scholarly journals Multi-objective Evolutionary Algorithms for Power Distribution System Optimal Reconfiguration

2019 ◽  
Vol 22 (3) ◽  
Author(s):  
Ivo Benitez Cattani
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Multi Objective Optimization ◽  
Power Losses ◽  
Nsga Ii ◽  
Power Distribution System ◽  
Multi Objective ◽  
Three Phase ◽  
Unbalanced Voltage

In this paper two reconfiguration methodologies for three-phase electric power distribution systems based on multi-objective optimization algorithms are developed in order to simultaneously optimize two objective functions, (1) power losses and (2) three-phase unbalanced voltage minimization. The proposed optimization involves only radial topology configurations which is the most common configuration in electric distribution systems. The formulation of the problem considers the radiality as a constraint, increasing the computational complexity. The Prim and Kruskal algorithms are tested to fix infeasible configurations. In distribution systems, the three-phase unbalanced voltage and power losses limit the power supply to the loads and may even cause overheating in distribution lines, transformers and other equipment. An alternative to solve this problem is through a reconfiguration process, by opening and/or closing switches altering the distribution system configuration under operation. Hence, in this work the three-phase unbalanced voltage and power losses in radial distribution systems are addressed as a multi-objective optimization problem, firstly, using a method based on weighted sum; and, secondly, implementing NSGA-II algorithm. An example of distribution system is presented to prove the effectiveness of the proposed method.

scholarly journals Evolutionary Multi-Objective Cost and Privacy Driven Load Morphing in Smart Electricity Grid Partition

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2470 ◽  
Author(s):  
Alamaniotis ◽  
Gatsis
Keyword(s):  
Smart Grid ◽  
Optimality Theory ◽  
Power Distribution ◽  
Distribution System ◽  
Electric Energy ◽  
Optimal Solution ◽  
Nsga Ii ◽  
Power Distribution System ◽  
Multi Objective ◽  
Grid Partition

Utilization of digital connectivity tools is the driving force behind the transformation of the power distribution system into a smart grid. This paper places itself in the smart grid domain where consumers exploit digital connectivity to form partitions within the grid. Every partition, which is independent but connected to the grid, has a set of goals associated with the consumption of electric energy. In this work, we consider that each partition aims at morphing the initial anticipated partition consumption in order to concurrently minimize the cost of consumption and ensure the privacy of its consumers. These goals are formulated as two objectives functions, i.e., a single objective for each goal, and subsequently determining a multi-objective problem. The solution to the problem is sought via an evolutionary algorithm, and more specifically, the non-dominated sorting genetic algorithm-II (NSGA-II). NSGA-II is able to locate an optimal solution by utilizing the Pareto optimality theory. The proposed load morphing methodology is tested on a set of real-world smart meter data put together to comprise partitions of various numbers of consumers. Results demonstrate the efficiency of the proposed morphing methodology as a mechanism to attain low cost and privacy for the overall grid partition.

Research on Identification Algorithm of Fragile Nodes: Based on Static and Dynamic Combination of Uncertainty in New Energy

2021 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Yingming Lin ◽  
Binjie Yan ◽  
Dongjian Gu
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Power Flow ◽  
Flow System ◽  
Wasserstein Distance ◽  
Identification Algorithm ◽  
Multi Objective Optimization ◽  
Power Distribution System ◽  
Multi Objective ◽  
New Energy

<p>In this work, <span style="font-family: 'Times New Roman';">t</span>aking the coupled 54-node power distribution system and 25-node power flow system as examples, the effectiveness of this method is verified. In addition, a multi-objective ADN joint planning model is established by means of Wasserstein distance measurement and K-medoid scenario analysis. The location, size RES, BESS and expansion schemes of distribution network based on this model are analyzed in detail, in order to provide scientific, reliable, and cost-maximized EVCS’s charging service capabilities. More importantly, we propose a multi-objective optimization algorithm−MONAA algorithm to solve the model.</p>

scholarly journals A novel approach of a dynamic multi objective optimization of a power distribution system

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Patrik Roger Ndjependa ◽  
Alexandre Teplaira Boum ◽  
Salomé Ndjakomo Essiane
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Dynamic Reconfiguration ◽  
Electrical Energy ◽  
Multi Objective Optimization ◽  
Power Losses ◽  
Power Distribution System ◽  
Available Energy ◽  
Voltage Deviation ◽  
System Average

AbstractA new dynamic multi objective optimization approach is covered in this paper. The technique for optimizing the power distribution system is dynamic reconfiguration. The goal is to propose an optimal dynamic reconfiguration which minimizes the active power losses and the voltage deviation of the nodes of the power distribution system according to the energy available at the source, while constantly guaranteeing the supply of the electrical energy to priority consumers. The reliability indices considered in this paper are the system average interruption frequency index (SAIFI) and the system average interruption duration index (SAIDI) and are used to check the reliability of the optimal configurations obtained. This study subdivides a day into periods. The variations in the available power of the source and the power requested by the load, cause a new optimal configuration of the network at each period. In this work, the load adapts to the source and the optimal network topology evolves according to the maximum available power of the source. A mathematical formulation of the dynamic optimization problem by period or piece is proposed. The dynamic approach consists in acquiring the power of the load and of the source by period or piece and to compare them. When the available energy is sufficient, an optimal configuration that minimizes the power losses and voltage deviation while ensuring the supply of electrical energy to all consumers in the network is proposed. On the other hand, when the available energy is insufficient, an optimal topology of the power system minimizing the power losses and voltage deviation while guaranteeing the supply of electrical energy to priority consumers of the network is proposed. The optimal solutions per period are obtained using the MIP and MINLP methods. The approach is implemented on standard IEEE 15, 33 and 69 node power distribution system. The results obtained are satisfactory and prove the effectiveness of this new vision for the conduct of the power distribution system.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Complete power distribution system representation and state determination for fault location

DYNA ◽  
2015 ◽  
Vol 82 (192) ◽  
pp. 141-149 ◽  
Author(s):  
Andres Felipe Panesso-Hernández ◽  
Juan Mora-Flórez ◽  
Sandra Pérez-Londoño
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Fault Location ◽  
Estimation Error ◽  
Distance Estimation ◽  
Power Distribution Systems ◽  
Line Load ◽  
Power Distribution System ◽  
Line Section

<p>The impedance-based approaches for fault location in power distribution systems determine a faulted line section. Next, these require of the estimation of the voltages and currents at one or both section line ends to exactly determine the fault location. It is a challenge because in most of the power distribution systems, measurements are only available at the main substation.  This document presents a modeling proposal of the power distribution system and an easy implementation method to estimate the voltages and currents at the faulted line section, using the measurements at the main substation, the line, load, transformer parameters and other serial and shunt connected devices and the power system topology. The approach here proposed is tested using a fault locator based on superimposed components, where the distance estimation error is lower than 1.5% in all of the cases. </p>

Robust Design of Power Distribution Systems Using an Enhanced Multi-Objective Genetic Algorithm

2012 ◽  
pp. 179-200 ◽  
Author(s):  
Cristiane G. Taroco ◽  
Eduardo G. Carrano ◽  
Oriane M. Neto
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Efficient Solutions ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Robust Solutions ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Reliability And Robustness

The growing importance of electric distribution systems justifies new investments in their expansion and evolution. It is well known in the literature that optimization techniques can provide better allocation of the financial resources available for such a task, reducing total installation costs and power losses. In this work, the NSGA-II algorithm is used for obtaining a set of efficient solutions with regard to three objective functions, that is cost, reliability, and robustness. Initially, a most likely load scenario is considered for simulation. Next, the performances of the solutions achieved by the NSGA-II are evaluated under different load scenarios, which are generated by means of Monte Carlo Simulations. A Multi-objective Sensitivity Analysis is performed for selecting the most robust solutions. Finally, those solutions are submitted to a local search algorithm to estimate a Pareto set composed of just robust solutions only.

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