Network Reconfiguration In Distribution Systems Research Articles

A Probabilistic Optimization Technique for Network Reconfiguration in Distribution System with PVs and Phasor Measurement Units

A Probabilistic Optimization Technique for Network Reconfiguration in Distribution System with PVs and Phasor Measurement Units

Optimal H2 Production and Consumption for Improved Utility Operations: Path to Net-Zero Emission Energy Production

Due to population growth, electricity demand increases significantly, and a continued reliance on fossil fuels will contribute to the global warming crisis. According to the U.S. Energy Information Administration, electricity production accounts for 33% of annual carbon dioxide (CO2) emissions of which 65% of this amount is produced by large-scale coal and natural gas power plants [1]. As a consequence, the global temperature is estimated to rise about 1.5°C to 2°C on average by the year 2050. To that end, the U.S. government set a nationwide Net-Zero Emission goal by the year 2050 in which the power sector, especially utilities and generation companies must supply their load with green energy by 2035, and the transportation sector must be electrified completely by 2050 [2]. Additionally, due to the advancements in distributed energy resources (DERs) technologies, such as solar, wind, storage, hydrogen (H2), and demand response programs, the capital costs of these technologies will drop by 60%-70% until 2050 according to the National Renewable Energy Lab’s (NREL) reports, accelerating the growing trend of utilizing more DERs [3].In recent years, H2 energy has demonstrated a great potential for large deployment from economic, environmental, and technical viewpoints. Generally, H2 energy can be produced, compressed, stored, and consumed using an electrolyzer, a compressor, a storage tank, and a fuel cell (FC) [4]. There are various technologies for water electrolysis such as alkaline, proton exchange membrane (PEM), and solid oxide electrolysis, in which electricity is used to separate water into oxygen and hydrogen. The generated H2 can then be compressed and stored in a storage tank, in the form of cryogenic liquid or high-pressure gas. The most important applications of H2 energy are 1) power generation with stationary/mobile FC units; 2) transportation fuel for light- and heavy-duty FC vehicles; 3) fuel for residential and commercial buildings (e.g., space and water heating); 4) feedstock for ammonia production, etc., 5) assist utilities with technical concerns such as PV smoothing, voltage, and frequency regulations, etc. [5] [6].In this study, we consider the perspective of the distribution system operator (DSO) that manages the DERs, especially H2 production and consumption by H2 systems, to reach the goal of net-zero emission energy production. It should be mentioned that a vertically integrated design is considered for the operation of the distribution network. To have realistic analysis of distribution network considering the power flow and voltage challenges, a standard 33-node distribution network [7] based on Fig. 1 including utility-operated natural gas power plants (combined cycle units and combustion turbine units), PV units, Battery energy storage (e.g., Li-ion batteries, Vanadium Redox flow batteries, etc.), and H2 systems (including electrolyzers, compressors, storage tanks, and FC units) are considered. Different types of voltage-dependent loads are considered such as critical, moderately critical, and non-critical loads to resemble load types like hospitals, offices, grocery stores, etc. The goal of normal operation from grid operators' (utilities) perspective is to operate these assets to minimize the total operational and investment costs and maximize the green energy production for the power sector. Interested readers are encouraged to check [8] for more information.Simulation results for different case studies assume costs for the year 2050, and demonstrate that with considering H2 systems and Redox flow batteries, the net-zero emission energy production for electricity demand supply is achieved in high PV penetration levels while addressing the technical and physical network constraints.[1] “U.S. Energy Information Administration,” [Online].https://www.eia.gov/tools/faqs/faq.php?id=77&t=11.[2] “International Energy Agency,” [Online].https://www.iea.org/reports/net-zero-by-2050.[3] L. J. Vimmerstedt, C. R. Augustine, P. C. Beiter, W. J. Cole, D. J. Feldman, P. Kurup, E. J. Lantz, R. M. Margolis, T. J. Stehly, C. S. Turchiet al., “2018annual technology baseline (atb),” National Renewable Energy Lab.(NREL), Golden, CO (United States), Tech. Rep., 2018.[4] H. Haggi, W. Sun, J. M. Fenton, and P. Brooker, “Risk-averse cooperative operation of PV and hydrogen systems in active distribution networks, ”IEEE Systems Journal, 2021.[5] A. Kovaˇc, M. Paranos, and D. Marciuˇs, “Hydrogen in energy transition: A review,” International Journal of Hydrogen Energy, 2021.[6] “Road Map to US Hydrogen Economy,” [Online].http://www.fchea.org/us-hydrogen-study.html.[7] M. E. Baran and F. F. Wu, “Network reconfiguration in distribution systems for loss reduction and load balancing,” IEEE Power Engineering Review, vol. 9, no. 4, pp. 101–102, 1989.[8] H. Haggi, W. Sun, J. M. Fenton, and P. Brooker, “Proactive scheduling of hydrogen systems for resilience enhancement of distribution networks,”2021IEEE Kansas Power and Energy Conference (KPEC), 2021. Figure 1

A coordinated restoration method of electric buses and network reconfiguration in distribution systems under extreme events

A coordinated restoration method of electric buses and network reconfiguration in distribution systems under extreme events

Optimum Location and Sizing of DG with Network Reconfiguration in Distribution System

new technique for energy loss reduction for distribution networks is obtainable. It is based onnetwork reconfigurationand algorithms for radial network study. A method for the reconfiguration of distribution system with Distributed Generation (DG) since consistency and power loss is suggested. in this paper below ordinary working situations. Primarily a BPSO algorithm based tie-switches location is conceded out at end nodes taking physical limitations and then preceded by fixing and sizing of DG at the tie-switches location usingFBS optimization method. Before reconfiguration, tie-switch will be in open situation. Reliability at load points is calculated using load flow analysis.Energetic coding is used for discovery the minimal shortcut path from resource to the load. A discover algorithm has been formulate for the network reconfiguration difficulty, since tie-switch and DGs for loss minimization and reliability to improve the load necessity, power stability equations and voltage parameters. The planned approach has been tested on IEEE 33-node radial distribution Networks systems.

Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

Mobile energy storage systems (MESSs) provide promising solutions to enhance distribution system resilience in terms of mobility and flexibility. This paper proposes a rolling integrated service restoration strategy to minimize the total system cost by coordinating the scheduling of MESS fleets, resource dispatching of microgrids and network reconfiguration of distribution systems. The integrated strategy takes into account damage and repair to both the roads in transportation networks and the branches in distribution systems. The uncertainties in load consumption and the status of roads and branches are modeled as scenario trees using Monte Carlo simulation method. The operation strategy of MESSs is modeled by a stochastic multi-layer time-space network technique. A rolling optimization framework is adopted to dynamically update system damage, and the coordinated scheduling at each time interval over the prediction horizon is formulated as a two-stage stochastic mixed-integer linear program with temporal-spatial and operation constraints. The proposed model is verified on two integrated test systems, one is with Sioux Falls transportation network and four 33-bus distribution systems, and the other is the Singapore transportation network-based test system connecting six 33-bus distribution systems. The results demonstrate the effectiveness of MESS mobility to enhance distribution system resilience due to the coordination of mobile and stationary resources.

Meta‐heuristic technique for network reconfiguration in distribution system with photovoltaic and D‐STATCOM

This study presents a reconfiguration methodology based on a multi-objective modified flower pollination algorithm (MO-MFPA) that aims to achieve the power loss reduction, minimum load balancing index, and maximum voltage profile in radial distribution networks with photovoltaic (PV) arrays and distribution static compensator (D-STATCOM). Here, PV array is considered as distributed generation and D-STATCOM acts as a distribution flexible AC transmission system. The MO-MFPA is a meta-heuristic technique based on the combination of flower pollination algorithm and cloning selection algorithm. A reconfiguration is done through changing the tie and sectional line positions in the distribution system. At the time of reconfiguration, movement of load node to a set of power nodes secures the radial structure of the network. Voltage stability index is used to pre-identify the most candidate buses for placing PV arrays and D-STATCOM. Then the proposed MO-MFPA is employed to deduce the size and locations of PV arrays and D-STATCOM from the elected buses. For more practical applications, different cases of reconfiguration, PV, and D-STATCOM installation are considered to evaluate the performance approach at different load factors. The proposed method has been effectively tested on IEEE 33, 69, and 118-bus distribution systems and encouraging results have been obtained.

Voltage and reactive power control in distribution network considering optimal network configuration and voltage security constraints

In order to reduce energy losses and improve voltage stability index in distribution system, two different approaches have been proposed and employed including voltage and reactive power control (volt/var control) and distribution network reconfiguration. In the present paper, volt/var control and network reconfiguration in distribution system considering voltage security constraints is modelled as a multi-objective optimization problem. Total electrical energy losses, voltages deviations and voltage stability have been considered as objectives. Also, a new method for distribution network reconfiguration has been utilized for implementation of these two problems simultaneously. In this way, the two problems can be solved in less time. In addition, different nature of loads in each bus is considered in network load modelling. Non-dominated sorting genetic algorithm-II is used to solve this problem. Finally, the effectiveness of the proposed method is evaluated by implementation on the IEEE 33-bus system and a real 77-bus distribution system.

Optimal network reconfiguration in distribution system for loss reduction and voltage-profile improvement using hybrid algorithm of PSO and ACO

Optimal network reconfiguration in distribution system for loss reduction and voltage-profile improvement using hybrid algorithm of PSO and ACO

Multi-Objective Approach for Reconfiguration of Distribution Systems with Distributed Generations

This paper presents a fuzzy multi-objective based heuristic algorithm for network reconfiguration of distribution systems considering distributed generations (DGs). The objectives of reduction of real power loss, branch current carrying capacity limit, maximum and minimum voltage constraints, and feeder load balancing are considered for performance enhancement of the distribution system. Since these objectives are non-commensurable and difficult to solve simultaneously using conventional approaches, they are converted into fuzzy domain and a fuzzy multi-objective function is formulated. A sensitivity analysis based on voltage profile improvement and real power loss reduction is used for obtaining optimal locations of DGs and genetic algorithm is used for optimal sizing of DGs. The proposed reconfiguration algorithm is implemented in two stages, initially in the first stage without incorporating DGs and in the second stage incorporating DGs for obtaining an optimal distribution system network reconfiguration. The advantage of the proposed method is demonstrated through a seventy node four feeders and a sixteen node three feeders distribution systems.

A Genetic Algorithm Approach for Optimal Distribution System Network Reconfiguration

Electrical energy is an essential ingredient for the industrial and all-round development of any country. Power distribution systems are radial in configuration and this makes the networks hard to manage, thus, the need for optimization. This paper presents the optimization of network reconfiguration of distribution system using genetic algorithm to get the optimal switching scheme for network reconfiguration with objective function to reduce power loss and improve active power of the system. Load flow for the network reconfiguration problem was formulated as single objective optimization problem. The optimization model was simulated using MATLAB/SIMULINK and validated on standard IEEE 13-bus and 25-bus distribution test feeders. The result shows that active power increases by 91.1% (1.6469p.u.) while the power loss reduced by 99.4% (1.6372p.u.) for 13-bus system. For 25-bus system, active power increased by 27% (0.9154p.u.) and power loss reduced by 96.2% (4.3074p.u.) after optimization. The results provide solutions to the power distribution system for the optimal switching scheme for network reconfiguration with improvement in active power of the system. Total real power loss was minimized according to the corresponding fitness values of the genetic algorithm solutions. The paper provides technical information that could help in the future expansion and operation planning of the power distribution network.

The Impacts of Distributed Energy Sources on Distribution Network Reconfiguration

Thanks to the recent improvements in renewable energy technologies throughout the world, distributed energy sources are now playing an undeniable role in supplying the electricity in distribution networks. This paper studies the impacts of utilizing distributed generation units on the task of network reconfiguration in distribution systems. Considering the importance of reducing voltage drops and voltage sags in distribution systems, network reconfiguration is formulated as a multiobjective optimization problem in this study to minimize these two objective functions. A Pareto-based metaheuristic optimization algorithm is proposed to identify a Pareto frontier representing the alternative high-quality suboptimal configurations. The proposed optimization method is tested on a 69-bus distribution system to demonstrate the performance of the algorithm.

Genetic Algorithm Based Network Reconfiguration in Distribution Systems with Multiple DGs for Time Varying Loads

Abstract This paper describes the implementation of an algorithm which predicts optimum reconfiguration plan for power distribution system with multiple PV generators. Since network reconfiguration is a multi objective and multi constrained problem, genetic algorithm is used for optimization. Forward backward load flow method with time varying load condition is considered. The objective function of the genetic algorithm incorporates all the objectives and constraints required for the reconfiguration plan. The algorithm developed predicts the switching pattern for reconfiguration which gives minimum loss and minimum voltage deviation. It also reduces the number of switching operations along with satisfying the defined limit constraints.

Network Reconfiguration in Distribution System by Software Simulation for Loss Reduction

The main aim of the distribution companies is to reduce their operating costs to get ahead of competition. One of the most popular approach is to increase the degree of reliability of distribution system. The management of network defeats (e.g. earth fault, short circuits) offers a lot of feasibilities for automation. The main jobs are fault localization, fault detachment and system refurbishing. The network manipulator needs excellent knowledge about the controlled network area to accomplish these tasks efficiently. In this paper a fault management system is described which magnifies the reliability of the system with the help of network reconfiguration. The fault localization, segregation and refurbishing allowance to remedy the operator from these demanding tasks during network defeats. This paper present a CYMDIST based analysis for the loss minimization problem. This method is tested in 11 KV distribution systems for loss minimization.

Adaptive Relay Setting for Distribution Systems Considering Operation Scenarios of Wind Generators

This paper presents a method for an adaptive relay setting for distribution systems with wind generators (WGs). The advanced distribution automation system (ADAS) is applied to monitor the operational status of WGs and line switches. For the change of operational status of WGs or network reconfiguration of distribution systems because of the operation of line switches, the function of the adaptive relay setting is activated by the ADAS control master station. Short-circuit analysis is performed to solve the magnitude and direction of fault-current flows. The protective relay settings are then accordingly revised and loaded to the protective relays along the feeder to achieve the adaptive fault protection. Sample distribution feeders with open- and closed-loop configurations are used to demonstrate the adaptive relay setting for distribution systems with various operational scenarios of WGs. It is concluded that the fault currents contributed by WGs must be included in the design of the tap/level settings of protective relays by the ADAS to achieve good protection of smart distribution systems.

Evolutionary Algorithm for Network Reconfiguration in Distribution Systems Considering Thermal Operational Conditions

This article presents a methodology for the development of an evolutionary algorithm (EA) applied to the reconfiguration of radial distribution systems. The EA uses an integrated thermal and electric model (ITM) to evaluate the fitness function. Initially, the ITM calculates steady-state temperature of each conductor and, consequently, their electric impedance. ITM can be used to assess overhead and underground networks. This assessment is done efficiently to obtain the electric losses in each topology obtained by EA. On the one hand, the ITM is applied to two real distribution networks: an underground of 144 bars and another overhead of 1,311 bars. Results show that there is a divergence from 3 to 17 % when the ITM is used during electric losses evaluation. On the other hand, EA is applied to two overhead distribution networks of 14 and 135 bars. The solutions obtained are feasible and with electric losses approx. 14 % lower than that of the initial topology.

Distribution Network Reconfiguration for Loss Reduction by Hybrid Differential Evolution

This article introduces a hybrid differential evolution (HDE) method for dealing with optimal network reconfiguration aiming at power loss reduction. The network reconfiguration of distribution systems is to recognize beneficial load transfers so that the objective function composed of power losses is minimized and the prescribed voltage limits are satisfied. The proposed method determines the proper system topology that reduces the power loss according to a load pattern. Mathematically, the problem of this research is a nonlinear programming problem with integer variables. This article presents a new approach that employs the HDE algorithm with integer variables to solve the problem. One three-feeder distribution system from the literature and one practical distribution network of Taiwan Power Company are used to exemplify the performance of the proposed method. Two other methods, the genetic algorithm and the simulated annealing, are also employed to solve the problem. Numerical results show that the proposed method is better than the other two methods.

Variable Scaling Hybrid Differential Evolution for Solving Network Reconfiguration of Distribution Systems

This paper presents an effective method-variable scaling hybrid differential evolution (VSHDE)-for solving the network reconfiguration for power loss reduction and voltage profit enhancement of distribution systems. The network reconfiguration of distribution systems is to beneficially recognize load transfers so that the objective function composed of power losses is minimized and the prescribed voltage limits are satisfied. The variable scaling factor based on the 1/5 success rule is used in the VSHDE method to overcome the drawback of the fixed and random scaling factor and alleviate the problem of the selection of a mutation operator in the hybrid differential evolution (HDE). One three-feeder distribution system from the literature and one practical distribution network of Taiwan Power Company (TPC) are used to compare the performance of the proposed method with the HDE, genetic algorithms (GAs), and simulated annealing (SA). Numerical results show that the performance of the proposed method is better than the other methods.

Application of Ant Colony Algorithm for Network Reconfiguration in Distribution Systems

This paper presents an efficient algorithm for the loss minimization by automatic sectionalizing switch operation in distribution systems. Ant colony algorithm is a multi-agent system in which the behaviour of each single agent, called artificial ant, is inspired by the behaviour of real ants. Ant colony algorithm is suitable for combinatorial optimization. The proposed methodology with some modification to the ant colony algorithm improves the computation time and convergence property. Numerical examples demonstrate the validity and effectiveness of the proposed methodology on a 32 bus system and a KEPCO 148 bus system.

Feeder Reconfiguration Using Cyclic Best-First Search

Network reconfiguration in distribution systems is realized by changing the status of sectionalizing switches, and is usually done for loss reduction or load balancing in the system. This paper presents an effective heuristic based switching scheme to solve the distribution feeder loss reduction problem. The proposed algorithm consists of two parts. One is to set up a decision tree to represent the various switching operations available. Another is to apply a proposed technique called cyclic best frrst search. The proposed algorithm identifies the most effective the set of switch status configuration of distribution system for loss reduction. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the 32, 69 bus system models.

Network reconfiguration of distribution systems using improved mixed-integer hybrid differential evolution

Network reconfiguration of distribution systems using improved mixed-integer hybrid differential evolution