Storm Impact Prediction for Grids: A System for Distribution Networks

A new method for online evaluation of the effects of PV panels and comparison with MVDI in electrical power distribution networks

Background: This field work practice requires that students be able to understand electricity systems in general, including generation, transmission, distribution, and load management processes Identification problems: Balak LBS transfer to Recloser improves delivery system reliability, efficiency, equipment life, and supply availability by enabling automatic disconnection and circuit recovery. Methods: Repairs to the LBSM system and replacement of feeders in Balak Village are urgently needed. Results: The results of the analysis of disturbances in the LBSM system in the 20kV SUTM distribution network are a reference for developing and improving systems in the distribution network. Conclusions:. The Balak LBSM system in the 20kV SUTM distribution network is susceptible to disturbances due to environmental factors, impacting reliability and efficiency during outages, with automatic Recloser system reducing losses.

The proliferation of distributed generation (DG) poses new challenges in management of voltages in distribution networks. Excess generation by DG systems can cause voltage rise and reverse power flows, changing the paradigm of unidirectional power flow in distribution networks. Among many mitigation strategies, volt/var control methods that utilise inverter-interfaced DG systems to rectify voltage issues would be beneficial not only because DG system are typically located closer to customers, but the inverters can also provide fast response in contrast to mechanically operating volt/var control devices. As yet, DG owners only generate revenues from the production of active power while no incentives are provided for reactive power import/export, signifying the need for an update in the market structure to follow the growth of inverter-interfaced DG systems in distribution networks. This paper aims to propose an economic incentive scheme for utilising the full capacity of photovoltaic (PV) systems in Australian distribution networks. A ‘lost opportunity’ market structure that considers non-unity power factor operation of PV inverters in volt/var control strategies is proposed. The results show that the proposed market structure can encourage participation of domestic PV systems in volt/var control by providing a win-win solution for all stakeholders in a distribution network.

The presence of distributed generation (DG), represented by photovoltaic generation and wind generation, brings new challenges to distribution network operation. To accommodate the integration of DG, this study proposes a bi‐level optimisation model to determine the optimal installation site and the optimal capacity of battery energy storage system (BESS) in distribution network. The outer optimisation determines the optimal site and capacity of BESS aiming at minimising total net present value (NPV) of the distribution network within the project life cycle. Then optimal power flow (OPF) and BESS capacity adjustment are implemented in the inner optimisation. OPF optimises the scheduling of BESS and network losses. On the basis of optimal scheduling of BESS, a novel capacity adjustment method is further proposed to achieve the optimal BESS capacity considering battery lifetime for minimising the NPV of BESS. Finally, the proposed method is performed on a modified IEEE 33‐bus system and proven to be more effective comparing with an existing method without BESS capacity adjustment.

The question of how energy storage can be used efficiently and effectively in distribution networks is open and ongoing. This work explores optimal allocation of battery energy storage systems (BESS) in distribution networks to maximize their support in integrating high penetration solar photovoltaics (PV). A genetic algorithm (GA)-based multi-layer multi-objective optimization model is developed that minimizes the voltage deviation caused by high PV penetration and decreases energy loss in the distribution system while also accounting for the BESS capital and operational lifetime. The optimization problem considers BESS unit capacities, BESS installation points in the network and the cumulative BESS capacity of the network as decision variables. Siting constraints that would play a practical role in resource allocation, such as construction limitations, environmental and visual impacts are not included in the model. A case study with the IEEE 8500-Node test feeder is carried out to discuss the effectiveness of the proposed method. The results show a clear connection between BESS sizing and siting decisions and voltage deviation reduction benefits in a distribution network.

This manuscript presents a case study to determine the optimal location and size of photovoltaic systems in an electric distribution networks using particle swarm optimization (PSO) such that network voltage profile is improved and losses are minimized. The distribution network of Masirah Island, Oman, is considered as a case study system. The test system is modeled and simulated using MATLAB load flow toolbox.

The living lab demonstration project PowerMatching City is a clear example of how distribution networks can take advantage of the increasing number of Distributed Energy Resources (DER). Due to the applied decentralized market model in this project, DER become active players on the local market. Battery energy storage systems are DER that can provide flexibility and grid support. This paper presents the design, analysis and implementation of In-Home Electricity Storage (IHES) systems in PowerMatching City. First, a bid strategy is developed that applies to the system constraints and the objective of profit maximization. Second, the effect of the integration of IHES systems in the local market on grid support services is analyzed. It is shown that integrating IHES systems in the distribution network reduces both the peak load and energy losses. Third, a field test is conducted, and the test results show that using the designed strategy the IHES systems are able to operate in a dynamic price market.

This study presents a bi‐level optimal sizing approach for hybrid energy storage system (HESS) in distribution network with high share of renewable energy. Differently from the traditional planning methods, the proposed two‐level approach can evaluate the investment risks caused by wind power uncertainty. In particular, the upper level describes the financial composition associated with HESS devices investment cost. The lower level searches optimal operation strategies for the minimal cost of each scenario set. The upper‐level and lower level models are bridged by CVaR, which measures the conditional tail expectation of lower level costs for the entire scenarios and are involved as the additional item of the upper objective. Moreover, to improve solution efficiency, some of the mathematics transformations including second‐order cone programming are adapted to transform the holistic non‐linear model into the more effective pattern that can be computed by the commercially available solver. The proposed method can compute the corresponding energy storage capacity based on the assessment of the risk tolerance of investors. Finally, a test system is used to validate the effectiveness of the proposed approaches.

This paper presents a new approach to the problem of defining an investment policy in battery energy storage systems in active distribution networks, taking into account a diversity of uncertainties. The proposed methodology allows the selection of type, capacity, and location of battery energy storage systems in distribution networks with distributed generation and electric vehicle charging stations. A mixed-integer stochastic programming problem is cunningly approached with a metaheuristic, where fitness calculation with stochastic scenarios is performed by introducing an approximation to the operation costs in the form of a polynomial neural network, generated according to the Group Method of Data Handling—GMDH method, with strong computing speeding-up. The quality of this approximation for heavy Monte Carlo simulations is assessed in a first case study using a 33-bus distribution test system. The optimization planning model is then validated in the same test system using real data collected from solar and wind sources, demand, prices, and charging stations. Four types of batteries are compared considering degradation impact. The results demonstrate the practicality and advantages of this process.

Integrating photovoltaic (PV) and battery energy storage systems (BESS) in modern power distribution networks presents opportunities and challenges, particularly in maintaining voltage stability and optimizing energy resources. This systematic review and bibliometric analysis investigates the coordination of smart inverter-enabled distributed energy resources (DERs) for enhancing PV-BESS integration and ensuring voltage stability. The study synthesizes recent advancements in smart inverter technologies, which provide grid support functions such as Volt/VAr control, and their applications in DER coordination. A comprehensive review of the literature is conducted to identify prevailing trends, research gaps, and emerging techniques in the field. Bibliometric analysis is employed to quantify the research landscape, highlighting key publications, citations, publications per country, and collaborative networks. The findings reveal that smart inverters play a crucial role in mitigating voltage violations and improving the hosting capacity of PV systems in distribution networks. Furthermore, optimal inverter settings, strategic placement of PV-BESS, and advanced control algorithms are identified as critical factors for effective DER integration. The study concludes by proposing future research directions, including the exploration of smart inverter interactions with legacy grid management systems and the development of robust algorithms for dynamic and adaptive DER coordination. This review serves as a valuable resource for researchers and practitioners aiming to enhance the stability and efficiency of power distribution networks through advanced DER management strategies.

Designing and installing efficient grounding systems in power distribution networks is considered a complex and crucial task to ensure the reliable operation of power-protective schemes while mitigating hazardous potentials arising from faults, thereby safeguarding both personnel and equipment. This paper aims to offer guidance on designing effective grounding systems in distribution networks by assessing the influence of parameters such as soil structure, fault current magnitude, and fault clearing time. This involves proposing a more precise methodology for calculating hazardous potentials, leveraging software tools like PowerFactory, to accurately determine short-circuit (SC) currents and fault clearing times at specific locations where grounding grids are to be installed. Consequently, Distribution System Operators (DSOs) can design tailored grounding systems that optimize techno-economic considerations without unnecessary over-dimensioning, accounting for the unique characteristics of the Medium-Voltage (MV) Line and soil structure.

Power grid vulnerability is not only associated with network frame structure and operation state, but also with the synergistic effect between information systems and physical systems. Based on complex-network theory, synergistic effect theory and risk utility theory, a multi-perspective collaborative vulnerability assessment method of active distribution network is proposed, which considers the effect of information systems. Firstly, the deterministic-stochastic topology model of distribution network and external disasters is established. Base on the panoramic information of systems, the physical information component failure probability under multiple time scale synergistic effects in disasters is determined. Secondly, considering the effect of information system in distribution network, a vulnerability assessment system in interactive mode of source network load under the active distribution network and information system integration, is established, and it accesses the vulnerability of active distribution network more comprehensive and specific. Finally, the rationality and validity of the multi-perspective collaborative vulnerability assessment method is verified by a regional distribution network. The result shows that this vulnerability assessment method can efficiently overcome the disadvantages in assessing power grid vulnerabilities from single perspective in the past time, and accord with the actual operation characteristics of current power grid.

In this paper we address the problem of optimal sizing of a given number of energy storage systems in a distribution network. These devices represent an effective solution for distribution system operators to prevent over- and undervoltages in distribution feeders. The sizing problem is first formulated in a two-stage stochastic framework in order to cope with uncertainty on future demand and distributed generation. By taking a scenario-based approach, this problem is then approximated in the form of a multi-scenario, multi-period optimal power flow. Since the size of the latter problem becomes rapidly prohibitive as the number of scenarios grows, a novel scenario reduction procedure is proposed. The procedure consists of solving a sequence of problems with scenario sets of increasing size. Tightness of the lower bound generated at each iteration can be checked very efficiently. Typically, a tight solution is obtained for sizes much smaller than that of the original scenario set. The algorithm is tested on the topology of a real Italian distribution network, using historical data of demand and generation to build the scenarios.

Due to the complex topology, multiple line branches, and dense spatial distributions of the distribution networks, the disturbances and failures cannot be eliminated it is difficult to completely avoid potential operation disturbances and faults. Thus, a reliable and stable protection system is necessary the protection system is bound to ensure a high level of reliability and stability. In that case, the monitoring and identification of the potential abnormal operation status of the protection system must be ensured the monitoring and identification of potential abnormal operation status of the protection system are facing new challenges. To this end, a data-driven-based real-time anomaly detection model is proposed in this paper. The kernel principal components analysis (KPCA) process is deployed to compress the dimensionality of raw data, which can then reduce the computational complexity within a high-dimensional data environment. Next, the isolated forest (IF) model is applied to excavate potential outliers according to the numeric range of the normal operating state of each feature. It can maintain high detection performance in the biased or sparse distributions and present a high reaction speed. Finally, the operation data of a relay system in a regional distribution network are utilized in the case study. The results verify the better performance of the proposed model in practical application, which can assist in the automatic identification and response of the risks of the distribution network.

A stochastic cost–benefit analysis framework for allocating energy storage system in distribution network for load leveling