Operation Of Power Distribution Networks Research Articles

Optimization Strategy for Electric Vehicle Routing under Traffic Impedance Guidance

Electric vehicles (EVs) not only serve as significant loads for the power grid but also play a crucial role in the operation of the traffic. Their travel and charging behaviors have an impact on both the power grid and the road network. In order to address the potential impacts of a large-scale deployment of EVs on the power grid and the exacerbation of traffic congestion, this paper first establishes a dynamic road network model based on graph theory and time-varying traffic data combined with a road impedance model. Then, the spatio-temporal distribution characteristics of EV travel are modeled. Furthermore, by incorporating real-time road network data, the traditional Dijkstra’s algorithm for finding the optimal path is improved. At each node, the current real-time road impedance is used as the objective for EV path updates, thus accurately capturing the energy consumption of the EVs. Finally, using a standard testing problem on a typical working day based on data from a real case, the impacts of EV travel and charging behaviors on power distribution network operation and traffic congestion are analyzed under scenarios with no guidance and guidance for the shortest travel time. The results show that this method can significantly reduce the time cost by approximately 18% in travel time, which is of particular concern to users. This method balances the load of the charging stations, elevates the voltage level within the safety requirement of 7%, and simultaneously alleviates traffic congestion near the stations.

Dynamic Modelling and Mutual Coordination of Electricity and Watershed Networks for Spatio-Temporal Operational Flexibility Enhancement Under Rainy Climates

This paper proposes a watershed-electricity nexus model to unlock the flexibility of watershed networks (WSNs) for supporting the operation of power distribution networks (PDNs) under rainy climates. The proposed model exploits the spatio-tem-poral flexibility of geographically dispersed pump clusters to pro-vide reserve services to PDNs, and a hyperbolic partial differential function derived from Saint-Venant hydrodynamic equations is formed to describe the dynamic processes of river stream flows. Be-sides, a flexibility evaluation method based on a composite sensitiv-ity matrix of water levels with respect to power injections is pre-sented to quantify the time-varying adjustable power domain of pump loads. Then, a multi-stage interactive coordinated scheduling strategy is developed for the mutual operation of WSNs and PDNs, where drainage pumps are jointly optimized to provide flexible power reserves, while an optimal PDN economic dispatch is per-formed to improve the power supply voltage of pump loads. Fur-thermore, an equivalent mixed-integer linear programming refor-mulation method is derived to cope with the original nonlinear par-tial differential optimization problem for computational tractabil-ity improvements. Comparative results have validated the effective-ness of the proposed strategy in eliminating voltage violations and shaving peak loads.

Spatio-Temporal Generative Adversarial Network Based Power Distribution Network State Estimation With Multiple Time-Scale Measurements

The increasing penetration of distributed renewable generation has introduced significant uncertainties and randomness to the power distribution network operation. Accurate and timely awareness of the network operation is of paramount importance to ensure system safety and reliability and is considered non-trivial and costly as substantial network reinforcement with advanced measurement devices is generally required. Also, the existing state estimation methods, e.g., weighted least square (WLS), may not converge in the presence of incomplete and inaccurate measurements. This paper proposes a spatio-temporal estimation generative adversarial network (ST-EGAN) consisting of feature extraction, information completion, data reconstruction and fake data discrimination to generate high-resolution pseudo-measurements to promote the accuracy and robustness of state estimation. The task of high-resolution power distribution network state estimation is carried out based on the mixed dataset of multiple time-scale measurements obtained from Supervisory Control and Data Acquisition (SCADA) and Phasor Measurement Units (PMU). The proposed solution is extensively assessed using the IEEE 33-bus test network compared with the existing solutions for a range of scenarios with different resolutions and noise intensities. The numerical results demonstrated that the proposed ST-EGAN can reduce the mean RMSE by 4.78% compared to interpolation algorithms, and reduce the RMSE by 0.14% and 0.21% compared with deep convolutional generative adversarial networks (DCGAN) and super-resolution convolutional networks (SRCNN) in the presence of noises with different intensities. The proposed method can be generalized to cases with different topological structures and measurement assembly conditions.

Evaluation of the solid-state breakers on the performance of power distribution grids with high-RES penetration

Electricity is currently one of the most promising components for the future growth of our communities. Energy consumption will skyrocket in the near future, necessitating massive reforms in the energy industry to ensure that contemporary cities have enough electricity. Furthermore, climate change necessitates a greater than ever before energy transition from fossil fuels to greener power generating sources such as wind, solar power, or other more newly discovered technologies such as hydrogen. However, significant improvements to the power distribution and transmission grids are required for high - RES penetration in the energy system. To illustrate, power networks have been built radially, with energy flowing in just one direction, from the original power source to the consumer, with no provision for the penetration of independent power producers (ipps) across power grids. As a result, studying and developing such significant components, including power protection systems, is now seen as a critical undertaking in order to minimize unanticipated breakdowns and optimize grid availability. The goal of this work is to analyze a novel and promising technology in the power protection industry known as Solid State Breakers (SSB) and its contribution to the efficient operation of power distribution networks with high-RES penetration.

Generalized User Equilibrium for Coordination of Coupled Power-Transportation Network

The increasing proliferation of electric vehicles (EVs) tightens the interaction between urban power distribution network (PDN) and transportation network (TN). This paper proposes the generalized user equilibrium (GUE) method for the coupled power-transportation network (CPTN) operation. First, the GUE concept is proposed to describe the steady traffic flow distribution as an extension of user equilibrium (UE), which could no longer exist due to the constraints placed by PDN operation on TN. Second, the GUE-based coordination model is established for CPTN with PDN generation scheduled and TN traffic assigned simultaneously. Finally, a decomposition method is developed to solve the model efficiently, which is converted into a master problem and a series of feasible/optimal path generation subproblems for individual origin-destination (O-D) pairs. The case studies on a real-world network have verified the effectiveness of the proposed model and method. The results demonstrate the necessity of GUE and its potential in improving the CPTN operation.

Robust island-mode operation of power distribution network using game theory for resilience enhancement

Robust island-mode operation of power distribution network using game theory for resilience enhancement

Technology balancing for reliable EV uptake in distribution grids: An Australian case study

The emergence of new technologies, such as photovoltaic (PV) solar systems, household Battery Energy Storage Systems (BESS) and electric vehicles (EVs), has introduced challenges for the Distribution Network Operators (DNOs) in the operation of power distribution networks. Uncontrolled renewable energy generation and storage, and EV charging can cause over/under voltage problems. Recently, there has been much effort, from control and scheduling of BESSs and EVs to PV curtailment, to address these issues. However, the knowledge about how much penetration of these technologies can be well-tolerated by the grid when all charging/discharging are uncontrolled, would still be of interest to DNOs. There are many depending factors such as customer consumption profiles, grid conditions and network constraints. In this paper, we propose a framework to determine the critical balance between PV, BESS and EV in a distribution grid. Using real data from 4000 customers in Victoria, Australia, we find that in the absence of advanced control and scheduling algorithms, the best approach to prevent voltage violation in the grid is to keep the installation of PV and BESS balanced with the EV penetration. We also show that power export to the grid by EVs using the vehicle-to-home (V2H) technology may contribute to keeping the grid voltage in the standard range if 40%–80% of EVs are in the discharge mode in critical peak times. While complete coordination of PV, EV and BESS has not yet been fully realized in many networks, our methodology provides a framework for DNOs to perform optimised planning.

A Novel Scalable Reconfiguration Model for the Postdisaster Network Connectivity of Resilient Power Distribution Systems.

The resilient operation of power distribution networks requires efficient optimization models to enable situational awareness. One of the pivotal tools to enhance resilience is a network reconfiguration to ensure secure and reliable energy delivery while minimizing the number of disconnected loads in outage conditions. Power outages are caused by natural hazards, e.g., hurricanes, or system malfunction, e.g., line failure due to aging. In this paper, we first propose a distribution-network optimal power flow formulation (DOPF) and define a new resilience evaluation indicator, the demand satisfaction rate (DSR). DSR is the rate of satisfied load demand in the reconfigured network over the load demand satisfied in the DOPF. Then, we propose a novel model to efficiently find the optimal network reconfiguration by deploying sectionalizing switches during line outages that maximize resilience indicators. Moreover, we analyze a multiobjective scenario to maximize the DSR and minimize the number of utilized sectionalizing switches, which provides an efficient reconfiguration model preventing additional costs associated with closing unutilized sectionalizing switches. We tested our model on a virtually generated 33-bus distribution network and a real 234-bus power distribution network, demonstrating how using the sectionalizing switches can increase power accessibility in outage conditions.

Stabilisation of the power grid with a hydrogen energy buffer

Abstract West Pomeranian University of Technology in Szczecin, as a leader, along with the University of Szczecin and Enea Operator LLC, is implementing the R&D project ‘Development of an intelligent and automatic system for stabilising the operation of power distribution networks based on modular installations of a hydrogen energy buffer with the intention of utilising hydrogen’. Its goal is to build the first hydrogen energy buffer in Poland, whose task will be to stabilise the parameters of the power grid. The operating conditions of the power grid, and the impact of the energy buffer system on its stability, have been determined. The nominal parameters of the buffer elements were calculated and the place of its installation and the assumptions for its operation have been indicated. The buffer will be located in the 110 kV / 15 kV substation.

Noncooperative Equilibrium-Seeking in Distributed Energy Systems Under AC Power Flow Nonlinear Constraints

Power distribution grids are commonly controlled through centralized approaches, such as the optimal power flow. However, the current pervasive deployment of distributed renewable energy sources and the increasing growth of active players, providing ancillary services to the grid, have made these centralized frameworks no longer appropriate. In this context, we propose a novel noncooperative control mechanism for optimally regulating the operation of power distribution networks equipped with traditional loads, distributed generation, and active users. The latter, also known as prosumers, contribute to the grid optimization process by leveraging their flexible demand, dispatchable generation capability, and/or energy storage potential. Active users participate in a noncooperative liberalized market designed to increase the penetration of renewable generation and improve the predictability of power injection from the high-voltage grid. The novelty of our game-theoretical approach consists in incorporating economic factors as well as physical constraints and grid stability aspects. Finally, by integrating the proposed framework into a rolling-horizon approach, we show its effectiveness and resiliency through numerical experiments.

The significance of formal & legal factors in selecting a location for a hydrogen buffer to stabilize the operation of power distribution networks

This article presents the conceptual assumptions for the process of identifying and evaluating the formal & legal factors that impact the choice of a hydrogen buffer location to stabilize the operation of power distribution networks. The assumption for the research process was establishing a methodological framework for an in-depth analysis of legislative acts (the EU legislation and the national law) to enable identification of synthetic groups of formal & legal factors to be further analyzed using the DEMATEL method. As a result, the cause-and-effect relations between the variables were examined, and an in-depth analysis was carried out to investigate the level of impact of the formal & legal factors on the functioning and location of a hydrogen energy buffer.

A dynamic optimization method for power distribution network operation with high ratio photovoltaics

With the high ratio distributed photovoltaics (PVs) penetration to the distribution network (DN), the bearing capacity, integration capacity, consuming capacity and controlling capacity of DN for PVs are all facing great challenges. Enhancing the flexible regulation and operation optimization capabilities of DN have become key factors to satisfy these new challenges. For the operation optimization problem of high ratio PVs penetration, a novel quasi-equal curtailment ratio (QCR) constraint of PVs is proposed in the dynamic optimization method for DN operation. Firstly, the uncertainty of high ratio PVs and their active power deviations are discussed. And a dynamic optimization framework of PVs based on optimal power flow (OPF) has been proposed. Secondly, the optimization model for high ratio PVs is formulated with multi-objective of maximum PVs output, minimum voltage deviation and minimum line loss, under the equality and inequality constraints of power flow, PVs power generation limit, QCR of PVs and so on. Then the multi-objective optimization problem (MOP) is transformed into a single-objective optimization problem (SOP) by weighting coefficients, and solved by sequential quadratic programming (SQP) with trust-region (TR) searching algorithm. Finally, the proposed method is tested, verified and compared with the primal dual interior point (PDIP) and traditional SQP algorithms in IEEE 33-bus, PG&E 69-bus, 292-bus and 1180-bus test cases. The experimental results show the rapidity and robustness of the proposed method.

Adaptive fuzzy directional bat algorithm for the optimal coordination of protection systems based on directional overcurrent relays

Despite bringing several benefits to modern power systems, distributed generation (DG) and microgrids cause a significant impact on the operation of power distribution networks, especially with regard to the protection system. The topological evolution of power distribution networks comprising DG units and the islanding capacity of microgrids have lead to significant changes in the magnitudes of short-circuit currents, consequently affecting the reliability of protection systems in terms of loss of selectivity (false tripping and/or sympathetic tripping), sensitivity (blind protection), and dynamic response (delayed trip). In this new scenario, the adoption of smart protection systems capable of incorporating advanced control and protection mechanisms is of paramount importance for ensuring the automatic reconfiguration and restoration of the power grid when undesirable phenomena like faults occur. Considering this scenario, this work proposes a novel metaheuristic called adaptive fuzzy directional bat algorithm (AFDBA), which can calculate optimal settings for directional overcurrent relays (DOCRs) in any power grid topology without the need for tuning the initial parameters. The technique is applied to three case studies, that is, the 3-bus, 9-bus, and 30-bus test systems. The algorithm performance is compared with that of genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), bat algorithm (BA), and directional bat algorithm (DBA). The results evidence that the proposed approach has high convergence speed, high robustness, and acceptable computational burden, while providing the proper coordination of protection systems.

Research on Optimal Management of Power Distribution Network Operation and Repair

Research on Optimal Management of Power Distribution Network Operation and Repair

Resilient Operation of Electric Power Distribution Grids Under Progressive Wildfires

Wildfires have been growingly recognized as a prominent threat in regions with high temperatures during the summer. Power distribution systems, especially those passing through forest regions, are exposed and highly vulnerable to wildfires. This article provides a general formulation to enhance the operational resilience of power distribution networks equipped with renewable energy resources, e.g., wind and solar energy, micro turbines as well as energy storage systems when exposed to progressive wildfires. The wildfire incident is characterized comprehensively and the dynamic heat balance equations of power distribution branches are used to model the impacts of wildfires on overhead line conductors. A mixed-integer quadratic optimization formulation is applied to optimally operate and coordinate all local energy resources to reduce load outages and enhance the system resilience. The applied framework is evaluated on the IEEE 33-node test system. Comprehensive sensitivity analyses are conducted to assess the efficacy of the applied framework, where the numerical results reveal the resilient operation of power distribution networks in the face of wildfire emergencies.

Structural Model of Power Grid Stabilization in the Green Hydrogen Supply Chain System—Conceptual Assumptions

The paper presents the conceptual assumptions of research concerning the design of a theoretical multi-criteria model of a system architecture to stabilize the operation of power distribution networks based on a hydrogen energy buffer, taking into account the utility application of hydrogen. The basis of the research process was a systematic literature review using the technique of in-depth analysis of full-text articles and expert consultations. The structural model concept was described in two dimensions in which the identified variables were embedded. The first dimension includes the supply chain phases: procurement and production with warehousing and distribution. The second dimension takes into account a comprehensive and interdisciplinary approach and includes the following factors: technical, economic–logistical, locational, and formal–legal.

Quantized event-driven simulation for integrated energy systems with hybrid continuous-discrete dynamics

Effective simulation methods are becoming critically essential for the analysis of integrated energy systems (IESs) to reveal the interactions of multiple energy carriers. The incorporation of various energy technologies and numerous controllers make the IES a heterogeneous system, which poses new challenges to simulation methods. This paper focuses on the simulation of an IES with hybrid continuous-discrete properties and heterogeneous characteristics. First, a modified third-order quantized state system (MQSS3) method is proposed for the simulation of district heating systems (DHSs), in which quantized state system (QSS) and time-discretized integration are integrated to efficiently manage numerous discrete control actions. Second, an event-driven framework is established to integrate MQSS3 into the simulation of the electricity-heat integrated energy system (EH-IES). This framework enables the adoption of the most suitable models and algorithms for different systems to accommodate the heterogeneous properties of an IES. Case studies of an EH-IES with maximum 80% PV penetration and 210 buildings demonstrate that the dynamic interactions between the DHS and the power distribution network are accurately illustrated by the proposed simulation methods, in which MQSS3 indicates the highest simulation efficiency. It is also demonstrated in the simulation results that the flexibility from DHS can be utilized as demand-side resource to support the operation of power distribution network in aspects such as consuming the surplus PV generations.

Analysis of power distribution network operation without power cut based on actual engineering data

Distribution Network operation without power cut has gradually become the trend of the future distribution network construction, the investment in distribution network has increased year by year, carrying out the study on the analysis of distribution network operation without power cut, analyzing the benefit of distribution network operation without power cut, it is of great significance to provide suggestions for the future distribution network operation cost lean management. Based on the technical analysis of non-outage operation in distribution network, combined with the social benefits of non-outage operation, this paper gives some suggestions on strengthening the management of non-outage operation.

Research on electric power distribution network operation and evaluation under energy saving and emission reduction environment

This paper puts forward a four-step evaluation method based on data mining directly from information system under energy saving and emission reduction environment, including taking data, finding problems and putting forward measures. Through distribution network core indexes, an example was given to prove the method is scientific and practical.

Optimization of Energy Storage Capacity to Smooth Wind Power Fluctuation

The uncertainty and randomness of wind power generation bring hidden trouble to the safe operation of power distribution network. Combining energy storage system with wind power generation can effectively improve the output characteristics of wind power generation. In this paper, considering the investment cost of energy storage and the effect of suppressing the fluctuation of wind power output, the optimization of energy storage capacity under the scenario of wind power grid connection is studied. Firstly, the multi-objective capacity optimization model of the energy storage system is established to minimize the cost of the energy storage system and the variance of wind power system output equipped with energy storage. Then, the multi-objective optimization problem is transformed into a single objective optimization problem by introducing the weight coefficient of the objective function and the particle swarm optimization algorithm (PSO) is used to solve the problem. Finally, through the test of IEEE-33 bus distribution network system, the relationship curve between energy storage capacity and wind power fluctuation suppression effect is obtained. The results of numerical examples show the effectiveness of the proposed method.