Reconfiguration of distribution network using different optimization techniques

2020 ◽  
pp. 155-169
Keyword(s):  
Distribution Network ◽  
Optimization Techniques

A novel approach to increase the share of renewable purchase obligation for planning of distribution network including grid scale energy storage

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jitendra Singh Bhadoriya ◽  
Atma Ram Gupta
Keyword(s):  
Energy Storage ◽  
Objective Function ◽  
Distributed Generation ◽  
Carbon Emissions ◽  
Distribution Network ◽  
Clean Energy ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
Novel Approach ◽  
Demand Models

Abstract In recent times, producing electricity with lower carbon emissions has resulted in strong clean energy incorporation into the distribution network. The technical development of weather-driven renewable distributed generation units, the global approach to reducing pollution emissions, and the potential for independent power producers to engage in distribution network planning (DNP) based on the participation in the increasing share of renewable purchasing obligation (RPO) are some of the essential reasons for including renewable-based distributed generation (RBDG) as an expansion investment. The Grid-Scale Energy Storage System (GSESS) is proposed as a promising solution in the literature to boost the energy storage accompanied by RBDG and also to increase power generation. In this respect, the technological, economic, and environmental evaluation of the expansion of RBDG concerning the RPO is formulated in the objective function. Therefore, a novel approach to modeling the composite DNP problem in the regulated power system is proposed in this paper. The goal is to increase the allocation of PVDG, WTDG, and GSESS in DNP to improve the quicker retirement of the fossil fuel-based power plant to increase total profits for the distribution network operator (DNO), and improve the voltage deviation, reduce carbon emissions over a defined planning period. The increment in RPO and decrement in the power purchase agreement will help DNO to fulfill round-the-clock supply for all classes of consumers. A recently developed new metaheuristic transient search optimization (TSO) based on electrical storage elements’ stimulation behavior is implemented to find the optimal solution for multi-objective function. The balance between the exploration and exploitation capability makes the TSO suitable for the proposed power flow problem with PVDG, WTDG, and GSESS. For this research, the IEEE-33 and IEEE-69 low and medium bus distribution networks are considered under a defined load growth for planning duration with the distinct load demand models’ aggregation. The findings of the results after comparing with well-known optimization techniques DE and PSO confirm the feasibility of the method suggested.

scholarly journals Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions

2021 ◽  
Author(s):  
Chinmay Shah ◽  
Richard Wies
Keyword(s):  
Power Distribution ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
Power Distribution Networks ◽  
Power Distribution Network ◽  
High Penetration ◽  
Islanded Mode

The conventional power distribution network is being transformed drastically due to high penetration of renewable energy sources (RES) and energy storage. The optimal scheduling and dispatch is important to better harness the energy from intermittent RES. Traditional centralized optimization techniques limit the size of the problem and hence distributed techniques are adopted. The distributed optimization technique partitions the power distribution network into sub-networks which solves the local sub problem and exchanges information with the neighboring sub-networks for the global update. This paper presents an adaptive spectral graph partitioning algorithm based on vertex migration while maintaining computational load balanced for synchronization, active power balance and sub-network resiliency. The parameters that define the resiliency metrics of power distribution networks are discussed and leveraged for better operation of sub-networks in grid connected mode as well as islanded mode. The adaptive partition of the IEEE 123-bus network into resilient sub-networks is demonstrated in this paper.

scholarly journals Proposal of optimal operation strategy applied to water distribution network with statistical approach

2020 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Alex Takeo Yasumura Lima Silva ◽  
Fernando Das Graças Braga da Silva ◽  
André Carlos da Silva ◽  
José Antonio Tosta dos Reis ◽  
Claudio Lindemberg de Freitas ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Optimization Techniques ◽  
Experimental Techniques ◽  
Computational Optimization ◽  
Depth Analysis

 Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using statistics and the design of experimental tools and software. The proposed technique was applied to a theoretical network developed for the study. Preliminary simulations were accomplished using EPANET, representing the main causes of water and energy inefficiency in Brazilian sanitation companies. Some parameters were changed in applying this model, such as reservoir level, pipe diameter, pumping pressures, and valve-closing percentage. These values were established by the design of experimental techniques. As output, we obtained the equation of response surface, optimized, which resulted in values of established hydraulic parameters. From these data, the obtained parameters in computational optimization algorithms were applied, resulting in losses of 26.61%, improvement of 16.19 p.p. with regard to the network without optimization, establishing an operational strategy involving three pumps and a pressure-reducing valve.  We conclude that the association of optimization and the planning of experimental techniques constitutes an encouraging method to deal with the complexity of water-distribution network optimization.

scholarly journals A Mutual Technique for Reconfiguration of Feeder Network by Optimal Locating and Sizing of Distribution Generator

2019 ◽  
Vol 63 (4) ◽  
pp. 320-331
Author(s):  
Kothuri Ramakrishna ◽  
Basavaraja Banakara
Keyword(s):  
Radial Distribution ◽  
Reactive Power ◽  
Electrical Power ◽  
Distribution Network ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
Optimum Location ◽  
Algorithm Optimization ◽  
Electrical Power System ◽  
Comparison Results

Common technique has been discussed in this paper for the reconfiguration of feeder network by optimal location and measuring of Distribution Generator (DG) in electrical power system. The consolidated execution of both Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) strategies are the curiosity of the proposed strategy. The optimization techniques are utilized for optimizing the optimum location and DG capacity for radial distribution network. The BBO algorithm requires radial distribution network voltage, real and reactive power for deciding the optimum location and capacity of the DG. Here, the input parameters of BBO are classified into sub parameters and permitted as the PSO algorithm optimization process. The PSO develops the sub solution with the assistance of sub parameters by issue synthesis. For identifying the optimum location and capacity of DG the BBO movement and mutation process is applied for the sub solution of PSO. At that point the proposed mutual technique is actualized in the MATLAB/simulink platform and by contrasting it with the BBO and PSO systems the effectiveness is scrutinized. The comparison results demonstrate the predominance of the proposed approach and affirm its capability to comprehend the issue.

scholarly journals Technical note: Graph theory-based heuristics to aid in the implementation of optimized drinking water network sectorization

2022 ◽  
Author(s):  
Marius Møller Rokstad ◽  
Karel Antonie van Laarhoven
Keyword(s):  
Drinking Water ◽  
Water Distribution ◽  
Mathematical Problem ◽  
Distribution Network ◽  
Large City ◽  
Distribution Networks ◽  
Technical Note ◽  
Optimization Techniques ◽  
Actual Distribution ◽  
Drinking Water Distribution

Abstract. Drinking water distribution networks form an essential part of modern-day critical infrastructure. Sectorizing a network into district metered areas is a key technique for pressure management and water loss reduction. Sectorizing an existing network from scratch is, however, an exceedingly complex design task that designs in a well-studied general mathematical problem. Numerical optimization techniques such as evolutionary algorithms can be used to search for near-optimal solutions to such problems, but doing so within a reasonable timeframe remains an ongoing challenge. In this work, we introduce two heuristic tricks that use information of the network structure and information of the operational requirements of the drinking water distribution network to modify the basic evolutionary algorithm used to solve the general problem. These techniques not only reduce the time required to find good solutions, but also ensure that these solutions better match the requirements of drinking water practice. Both techniques were demonstrated by applying them in the sectorization of the actual distribution network of a large city.

scholarly journals A Discrete Simulation-Based Optimization Algorithm for the Design of Highly Responsive Last-Mile Distribution Networks

2021 ◽  
Author(s):  
André Snoeck ◽  
Matthias Winkenbach
Keyword(s):  
Network Design ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
On Demand ◽  
Distribution Network Design ◽  
Last Mile ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Congestion Effects

Online and omnichannel retailers are proposing increasingly tight delivery deadlines, moving toward instant on-demand delivery. To operate last-mile distribution systems with such tight delivery deadlines efficiently, defining the right strategic distribution network design is of paramount importance. However, this problem exceeds the complexity of the strategic design of traditional last-mile distribution networks for two main reasons: (1) the reduced time available for order handling and delivery and (2) the absence of a delivery cut-off time that clearly separates order collection and delivery periods. This renders state-of-the-art last-mile distribution network design models inappropriate, as they assume periodic order fulfillment based on a delivery cutoff. In this study, we propose a metamodel simulation-based optimization (SO) approach to strategically design last-mile distribution networks with tight delivery deadlines. Our methodology integrates an in-depth simulator with traditional optimization techniques by extending a traditional black-box SO algorithm with an analytical model that captures the underlying structure of the decision problem. Based on a numerical study inspired by the efforts of a global fashion company to introduce on-demand distribution with tight delivery deadlines in Manhattan, we show that our approach outperforms contemporary SO approaches as well as deterministic and stochastic programming methods. In particular, our method systematically yields network designs with superior expected cost performance. Furthermore, it converges to good solutions with a lower computational budget and is more consistent in finding high-quality solutions. We show how congestion effects in the processing of orders at facilities negatively impact the network performance through late delivery of orders and reduced potential for consolidation. In addition, we show that the sensitivity of the optimal network design to congestion effects in order processing at the facilities increases as delivery deadlines become increasingly tight.

scholarly journals Review on Distribution Network Optimization under Uncertainty

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3369 ◽  
Author(s):  
Huilian Liao
Keyword(s):  
Network Optimization ◽  
Optimization Problems ◽  
Distribution Network ◽  
Network Planning ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
Optimization Under Uncertainty ◽  
Distribution Network Planning ◽  
Optimization Search ◽  
Planning And Operation

With the increase of renewable energy in electricity generation and increased engagement from demand sides, distribution network planning and operation face great challenges in the provision of stable, secure and dedicated service under a high level of uncertainty in network behaviors. Distribution network planning and operation, at the same time, also benefit from the changes of current and future distribution networks in terms of the availability of increased resources, diversity, smartness, controllability and flexibility of the distribution networks. This paper reviews the critical optimization problems faced by distribution planning and operation, including how to cope with these changes, how to integrate an optimization process in a problem-solving framework to efficiently search for optimal strategy and how to optimize sources and flexibilities properly in order to achieve cost-effective operation and provide quality of services as required, among other factors. This paper also discusses the approaches to reduce the heavy computation load when solving large-scale network optimization problems, for instance by integrating the prior knowledge of network configuration in optimization search space. A number of optimization techniques have been reviewed and discussed in the paper. This paper also discusses the changes, challenges and opportunities in future distribution networks, analyzes the possible problems that will be faced by future network planning and operations and discusses the potential strategies to solve these optimization problems.

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