Topology Of Distribution System Research Articles

Model-free voltage control of active distribution system with PVs using surrogate model-based deep reinforcement learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

Optimal radial topology of electric unbalanced and balanced distribution system using improved coyote optimization algorithm for power loss reduction

Optimal radial topology of electric unbalanced and balanced distribution system using improved coyote optimization algorithm for power loss reduction

Mathematical optimization versus Metaheuristic techniques: A performance comparison for reconfiguration of distribution systems

Reconfiguration is a complex combinatorial problem in which the topology of distribution systems is modified by the opening/closing of interconnection switches aiming techno-economic benefits (e.g., minimization of losses). Numerous optimization methods have been developed to solve the reconfiguration problem, although a comparative analysis of their performances is still a challenging task due to the nature of the methods, differences in their implementation, and used computational equipment. To fulfill that gap, this paper assesses classical models along with metaheuristics already applied in the specialized literature considering the reported losses and computational effort. To eliminate differences due to implementation and equipment, two proposed metrics are assessed using a reference specialized power flow: ‘equivalent time’ and ‘equivalent number of power flows’. The quality of the solutions was compared for standard test systems (33, 136, and 417 buses) and a ranking of the methods was produced. It was concluded that linear and conic programming models find the optimal solution for low and medium-size systems; moreover, the linear model requires lower computational effort than the conic and the nonlinear programming formulations. On the other hand, it was verified that metaheuristics need lower computational effort and provide better solutions for large-size systems compared to classical optimization.

Key technologies for medium and low voltage DC distribution system

Development of the medium and low voltage DC distribution system is of great significance to a regional transmission of electric energy, increasing a penetration rate of new energy, and enhancing a safety of the operation of the AC/DC interconnected grid. This paper first summarizes the medium and low voltage DC distribution system schemes and plans put forward by many countries, and then elaborate status of under-construction medium and low voltage DC distribution system project cases in China. Based on these project cases, this paper analyzes key issues involved in the medium and low voltage DC distribution system topologies, equipment, operation control technologies and DC fault protections, in order to provide theoretical and technical reference for future medium and low voltage DC distribution system-related projects. Finally, this paper combines a current China research status to summarize and give a prediction about the future research direction of medium and low voltage DC distribution system, which can provide reference for the research of medium and low voltage DC distribution system.

Temporal Graph Super Resolution on Power Distribution Network Measurements

The applications of super-resolution (SR) technology in the field of image completion are successful. Nevertheless, industry applications demand not only image completion but also the topology and time-series completion. In this article, the SR technology on a topology graph is studied in the scenario of recovering measurements in power distribution systems for cost saving and security & stability improvement. The power flow and voltage magnitude measurements on feeders are reported at different frequencies. In this article, a new data completion method considering distribution system topology is proposed. Firstly, the graph convolutional neural network (GCN) is used for spatial-temporal convolution on a graph, and then the power system state estimation (SE) is used introducing the physical constraints. This method realizes the super-resolution of distribution system measurements, improves the state awareness of distribution systems. Hence, it helps to improve the efficiency of distribution network operation and to reduce equipment failures.

Methodology of solution for the distribution network reconfiguration problem based on improved harmony search algorithm

The topology of power distribution systems can be modified by altering the status of sectional and tie switches for load management and protection, while maintaining the required network radiality. Several effective optimisation algorithms and graph theory-based techniques for system radiality detection have been proposed in specialised literature to solve the distribution network reconfiguration problem, usually seeking to achieve power loss reductions and voltage profile improvements. This work aims to contribute to this line of research and its novelties are composed of proposing as solution method a methodology based in an enhanced version of harmony search metaheuristic called improved harmony search algorithm, and a new simple and effective system impedance matrix based process to detect islanding of nodes as a strategy to meet radiality constraint. The proposed methodologies were applied to 33-bus, 84-bus and 118-bus distribution networks known from technical literature, aiming to total active power loss minimisation. As comparison between methods, a key focus in analysis of results is related to discuss some advantages and effectiveness of improved harmony search over original harmony search algorithm to attain optimal radial topologies.

Loss Minimization by Reconfiguration along with Distributed Generator Placement at Radial Distribution System with Hybrid Optimization Techniques

In this paper a new methodology is used to reconfigure the topology of distribution system and placement of Distributed generators (DG) optimally. This methodology is adopted from the three optimization techniques which are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Blue Whale Optimization (BWO). The basic principles of the GA is used the optimal switching, the foundation for the swarm searching techniques, PSO is used to find the optimal placement and latest optimization technique, BWO is used to find the size of the type-III DG. The major objective of the paper is to minimize the losses through optimal reconfiguration and optimal placement of DG in balanced radial distribution system.

Robust PCA-deep belief network surrogate model for distribution system topology identification with DERs

With the expansion of distribution networks and increased penetration of distributed energy resources (DERs), it is becoming increasingly important to obtain accurate distribution network topology in real-time. In this paper, a robust principal component analysis coupled deep belief network (PCA-DBN) surrogate model is proposed for distribution system topology identification. It integrates the benefits of robust feature extraction from PCA to deal with data quality issues and filter out noise, and the strength of DBN in capturing the nonlinear relationship between voltage amplitudes and the binary states of switchable connections. This also significantly reduces the DBN training complexity without loss of accuracy. It is shown that the widely used standard deviation of voltage drop and the voltage covariance matrix features yield less accuracy as compared to that of the voltage amplitudes in presence of high penetration of DERs and ZIP loads. Comparison results with other alternatives, such as the random forest (RF), multi-output regression (MOR) and the traditional DBN methods demonstrate that the proposed method can achieve a much higher topology identification accuracy while maintaining robustness to missing data and measurement noise under various penetration levels of DERs.

Full-Scale Distribution System Topology Identification Using Markov Random Field

The identification of the distribution system topology is the key concern in distribution system state estimation and the precondition for its energy management. However, lacking sufficient measurement devices, full-scale identification of entire distribution grid can hardly be achievable in practice. The frequent topology changes in distribution systems impose challenges for topology identification. This paper proposes a novel topology identification method by deeply mining the data obtained from gird terminals and smart meters at end-users premises. The proposed method starts with data processing, followed by nodal correlation analysis and topology modeling based on the Markov Random Field (MRF) method, where the pseudo-likelihood method and L2 regularization theory are introduced to improve the computation efficiency while preventing the over-fitting problem. Then the iterative screening method is developed to generate the distribution system topology of medium/low-voltage distribution systems. Finally, the incremental learning and parallel programming models are proposed to implement the algorithms on single/multi-terminal. The effectiveness of the proposed model is validated on IEEE 33-node, IEEE 123-node and actual distribution systems.

High-speed directional protection without voltage sensors for distribution feeders with distributed generation integration based on the correlation of signals and machine learning

This paper proposes a novel methodology to define fault current direction along the Distribution Feeder (DF) considering Distributed Generation (DG) integration. The proposed methodology is based on Empirical Decomposition (ED), Decision Trees (DT) and Support Vector Machine (SVM). Using ED, it is possible to determine different Principal Components (PCs) that are used are inputs in these DT and SVP classifiers. Assessment of methodology considering different faults, inception angles, fault distances, and others are carried out. Besides, the proposed methodology is tested successfully considering different distribution system topologies and by analyzing special features required by relay manufacturers. Test results highlight the efficiency of the methodology, which presents a concise design and a simple mathematical formulation in the time domain.

Distributionally Robust Distribution Network Configuration Under Random Contingency

Topology design is a critical task for the reliability, economic operation, and resilience of distribution systems. This paper proposes a distributionally robust optimization (DRO) model for designing the topology of a new distribution system facing random contingencies (e.g., imposed by natural disasters). The proposed DRO model optimally configures the network topology and integrates distributed generation to effectively meet the loads. Moreover, we take into account the uncertainty of contingency. Using the moment information of distribution line failures, we construct an ambiguity set of the contingency probability distribution, and minimize the expected amount of load shedding with regard to the worst-case distribution within the ambiguity set. As compared with a classical robust optimization model, the DRO model explicitly considers the contingency uncertainty and so provides a less conservative configuration, yielding a better out-of-sample performance. We recast the proposed model to facilitate the column-and-constraint generation algorithm. We demonstrate the out-of-sample performance of the proposed approach in numerical case studies.

Optimal Low-voltage Distribution Topology with Integration of PV and Storage for Rural Electrification in Developing Countries: A Case Study of Cambodia

This paper addresses an optimal design of low-voltage (LV) distribution network for rural electrification considering photovoltaic (PV) and battery energy storage (BES). It aims at searching for an optimal topology of an LV distribution system as well as the siting and sizing of PV and storage over a time horizon of 30 years. Firstly, the shortest-path algorithm (SPA) and first-fit bin-packing algorithm (FFBPA) are used to search for the optimal radial topology that minimizes the total length of the distribution line and improves the load balancing. Then, the optimal siting of decentralized BES (DeBES) is determined using a genetic algorithm (GA) to eliminate the undervoltage constraints due to the load consumption. Two iterative techniques are elaborated to size the maximum peak power of PV and the minimum number of DeBES that can be connected to an LV network without violating the voltage and current constraints. Then, the sizing strategy of centralized BES (CeBES) is developed to avoid reverse power flows into the medium-voltage (MV) network. Finally, a Monte Carlo approach is used to study the impact of load profile uncertainties on the topology. A non-electrified village in Cambodia has been chosen as a case study.

Joint Estimation of Operational Topology and Outages for Unbalanced Power Distribution Systems

An electric power distribution system is operated in several distinct radial topologies by opening and closing of system's sectionalizing and tie switches. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). This paper presents a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. Specifically, a minimum weighted least absolute value estimator is proposed that uses the line flow measurements, historical/forecasted load data, and ping measurements and solves a mixed-integer linear program (MILP) to estimate the operational topology and any outaged sections simultaneously. We thoroughly validate the accuracy of the proposed approach using IEEE 123-bus and a 1069-bus three-phase multi-feeder test system with the help of numerous simulations. It is observed that the approach performs well even at high percentages of measurement errors.

Model-Free Optimal Voltage Phasor Regulation in Unbalanced Distribution Systems

The proliferation of voltage Phasor Measurement Units (PMUs) into electric power distribution grids presents new opportunities for utility operators to manage their systems more effectively. In particular, distribution-level PMUs can serve as proxy measurements for active and reactive power flows, thus alleviating the need for current transformer-based measurements for certain applications. In this work, we explore the use of distribution PMU measurements to optimally control line power flows without explicit measurements of these quantities and without a priori knowledge of the underlying distribution system topology. To do so, we extend a 2 dimensional Extremum Seeking (2D-ES) control paradigm to simultaneously manage Distributed Energy Resource (DER) active and reactive power contributions in unbalanced distribution systems. Simulation results show the ability of the proposed approach to virtually island different portions of a 3-phase unbalanced the network using DER injections while maintaining proper voltage magnitudes in the rest of the network.

Flexible AC Power Flow Control in Distribution Systems by Coordinated Control of Distributed Solar-PV and Battery Energy Storage Units

The flexible AC transmission systems (FACTS) have been used for controlling power flows in the transmission corridors to improve both the steady and dynamic states of operation. This paper proposes to extend the FACTS concept to power distribution systems, where the focus is in controlling renewable energy resources (RERs) and battery energy storage systems (BESSs) to provide a flexible AC power flow control in the distribution corridors of a medium voltage (MV) distribution system. The outputs of the proposed flexible AC power flow control system (FACPFCS) can be used to help the distribution network operator (DNO) to optimize the use of RERs and BESSs in the existing distribution grid to obtain the following benefits: congestion relief, sag reduction in long lines, mitigation of reverse power flow in the grid, deferral of distribution upgrade, Volt/VAr support, peak shaving, and a controllable storage bus that can act as a generator or load. To validate the proposed FACPFCS, simulation studies have been carried out using a practical radial distribution system topology derived from the electricity networks of New South Wales, Australia. The simulation results demonstrate that FACPFCS can provide an effective coordinated control of BESS and solar-PV units in the distribution systems to provide the mentioned benefits by controlling the power flows in the distribution lines.

Topology-Aware Vehicle-to-Grid Energy Trading for Active Distribution Systems

This paper proposes a topology-aware vehicle-to-grid (V2G) energy trading mechanism that uses charging/discharging powers of electric vehicles (EVs) to regulate voltage deviations of an active distribution system. To incentivize EVs to trade charging/discharging energy, auction theory is employed to guarantee three economic properties: 1) truthfulness; 2) individual rationality; and 3) social cost minimization. The mechanism is designed according to the topology of an active distribution system, in which multiple microgrids (MGs) are networked through a distribution network (DN). Two types of V2G auctions are proposed for the MG and DN, respectively. In each auction, the auctioneer optimizes control of EVs’ charging/discharging by solving a social cost minimization problem subject to constraints of power network topology. Further, the mechanism uses analytic target cascading framework, allowing the MG and DN to set up their own V2G auctions separately, and meanwhile enabling them to coordinate with each other to determine DN–MG power exchange. It is theoretically proved that the mechanism’s three economic properties hold in both the cases of grid-tied MGs and islanding MGs. Simulation results show that the proposed mechanism can regulate voltages of the distribution system to a secure range. Theoretic analysis of the economic properties is verified as well.

A Study on the Application of MVDC Technology to Expand the Hosting Capacity of Renewable Generation in Distribution System

Abstract The changes in the distribution system that will be brought about by the expansion of renewable energy sources are expected to be unacceptable only by the existing distribution system topology. Therefore, in order to realize the quantitative expansion based on the qualitative improvement of technology, this paper proposes combination of the planned solution to convert AC D/L to DC D/L and the operational solution to convert NOP to SOP.

ANALISIS DAN PERBANDINGAN WIRELESS DISTRIBUTION SYSTEM (WDS) DAN NON-WIRELESS DISTRIBUTION SYSTEM (NON-WDS) BERBASIS OPENWRT MENGGUNAKAN ACCESS POINT PADA JURUSAN TEKNIK INFORMATIKA FAKULTAS TEKNIK UNIVERSITAS HALU OLEO

The wireless network is one of the best alternatives in building a network of computers that is practical, in some agencies and the commercial wireless network is used to support an existing wired network. But its implementation is still used cable network that became the backbone of the access point so that a client that is connected can access the internet. Wiring problems can be a considerable obstacle in places that are hard to reach. The wireless distribution system is a system for developing a wireless internet network without having to use a cable as a backbone for the access point but instead of utilize a wireless line of the access point. At the time of the wireless distribution system network, topology and network topology of the non-wireless distribution system is applied, will be on analysis using Wireshark, the QoS parameter application that consists of a Delay, Throughput, and Packet Loss. The testing performed against the clients who are numbered six (6) is each connected to the access point. Scenario testing is done i.e. the conditions streaming and download, made during the three (3) days. Of test results obtained, the wireless distribution system network topology has the value throughput, delay; packet loss is a little less useful than a non-network topology wireless distribution system. But the differences in the average value of the QoS parameters that are generated are not too significant. Keywords — Wireless Distribution System, Non-Wireless Distribution System, Quality of Service ( QoS )

Novel Linearized Power Flow and Linearized OPF Models for Active Distribution Networks With Application in Distribution LMP

The locational marginal price (LMP) methodology has been discussed for distribution networks/systems under the smart grid initiative. In this paper, a new distribution LMP (DLMP) formulation is presented which includes reactive power prices and voltage constraints. To solve DLMP, three modeling tools, namely, linearized power flow for distribution (LPF-D), loss factors for distribution (LF-D), and linear optimal power flow for distribution (LOPF-D) are proposed. LPF-D solves not only voltage angles but also magnitudes through linear expression between bus injections and bus voltages, specifically for distribution systems. LF-D is solved recursively based on the radial topology of typical distribution systems. With the integration of LPF-D and LF-D, conventional optimal power flow (OPF) can be reformulated as LOPF-D which is essentially a linear programming model. Test results on various systems show that: 1) LPF-D efficiently yields very close results if compared with AC power flow; 2) LOPF-D provides very close dispatch results in both real and reactive power if compared with ACOPF; and 3) the proposed DLMPs calculated with LF-D and LOPF-D give accurate price information if compared with the prices from ACOPF. Further, these three tools are not limited to DLMP but can be potentially applied to other distribution analyses.

Island Partition of Distribution System with Distributed Generators Considering Protection of Vulnerable Nodes

To improve the reliability of power supply in the case of the fault of distribution system with multiple distributed generators (DGs) and reduce the influence of node voltage fluctuation on the stability of distribution system operation in power restoration, this paper proposes an island partition strategy of the distribution system considering the protection of vulnerable nodes. First of all, the electrical coupling coefficient of neighboring nodes is put forward according to distribution system topology and equivalent electrical impedance, and the power-dependence relationship between neighboring nodes is calculated based on the direction and level of the power flow between nodes. Then, the bidirectional transmission of the coupling features of neighboring nodes is realized through the modified PageRank algorithm, thus identifying the vulnerable nodes that have a large influence on the stability of distribution system operation. Next, combining the index of node vulnerability, an island partition model is constructed with the restoration of important loads as the primary goal. In addition, the mutually exclusive firefly algorithm (MEFA) is also proposed to realize the interaction of learning and competition among fireflies, thus enhancing the globally optimal solution search ability of the algorithm proposed. The proposed island partition method is verified with a Pacific Gas and Electric Company (PG and E) 60-node test system. Comparison with other methods demonstrates that the new method is feasible for the distribution system with multiple types of distributed generations and valid to enhance the stability and safety of the grid with a relatively power restoration ratio.