Distribution Network System Research Articles

Research on Integrated Energy Distributed Sharing in Distribution Network Considering AC Power Flow and Demand Response

Under the constraint of the AC power flow architecture considering reactive power regulation, the examination of integrated energy distributed transactions among multiple subsystems can promote the research in the field of energy sharing. It is difficult to fully cover the consideration of AC power flow, demand response, integrated energy, and other factors in traditional related research. In response, a study is therefore conducted in this paper on integrated energy sharing in the distribution network. First, this paper introduces the system operation framework of the proposed distribution network model, and explains the interaction between all the players. Secondly, a distribution network power flow model and an integrated energy subsystem model are respectively. In particular, the subsystem model specifically considers new energy, demand response, integrated energy, and other factors. Then, a cooperative game model is constructed based on the cooperative relationship among subsystems in the distribution network system, followed by the analysis of the benefits brought by cooperation to the distribution network and the subsystems themselves. Finally, a distributed solution flow is established for the model based on the Alternating Direction Method of Multipliers (ADMM) algorithm. The results of the example analysis reveal the effectiveness of the model proposed in increasing the degree of energy utilization and further absorbing new energy in the distribution network system, each subsystem can generate up to 12% more absorption capacity than it would otherwise operate separately to accommodate more renewable energy in the distribution system.

Photovoltaic injection power estimation method based on variable voltage sensitivity matrix

The operation of PVs has a significant impact on the safe and economic operation of the distribution networks. Nevertheless, there are many cases where the distribution system operators cannot obtain the accurate operation information of PVs. To solve the above problems, this paper proposes a PV injection power estimation method based on the variable voltage sensitivity matrix. First, the voltage sensitivity matrix is constructed. Second, all the node voltage magnitudes are obtained indirectly through distribution network state estimation owing to the limited number of voltage measurements. Then, combine the estimated voltages with the voltage sensitivity matrix to realize the estimation of PV injection power. Finally, the validity of the proposed method is verified in CIGRE distribution network, IEEE 34-node and IEEE 123-node distribution systems. The results show that PV on-grid state and output can be effectively identified in several different scenarios: PV continuous change, PV injection power plunge, and PV injection power plunge during continuous change. Furthermore, the performance of the proposed method is unaffected by the on/off-grid action of the impact load. The average error of PV injection power estimation results is less than 4 %, which has strong adaptability to operating conditions and good estimation accuracy.

Mutual entity authentication of quantum key distribution network system using authentication qubits

Entity authentication is crucial for ensuring secure quantum communication as it helps confirm the identity of participants before transmitting any confidential information. We propose a practical entity authentication protocol for quantum key distribution (QKD) network systems that utilizes authentication qubits. In this protocol, authentication qubits that are encoded with pre-shared information are generated and exchanged to verify the legitimacy of each entity. By using the authentication qubit, participants can identify each other with enhanced security level through the quantum channel. The proposed protocol can be easily integrated with existing QKD systems without the need for additional hardware. In this study, we demonstrated the efficacy of the proposed scheme using a 1xN QKD network system and verified its stable operation over a deployed fiber network. Additionally, a security analysis of the proposed entity authentication protocol and architecture is provided.

An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid

With the large-scale EV connected into the wind power grid, the intermittent, fluctuating and stability bring rigorous challenges for power quality and dispatch, thus wind curtailment becomes more serious. This paper proposes an advanced multi-objective collaborative scheduling strategy to improve the accuracy of the predictable wind grid and ensure the stable operation of the grid by optimizing wind power and EV synergistically. Firstly, a hybrid power prediction method is proposed based on density-based spatial clustering applied to noise (DBSCAN) and partial least squares regression (PLSR) combined with long and short-term memory neural network (LSTM). It establishes a linear component prediction mode to predict the nonlinear wind power efficiently. Secondly, a multi-objective optimization scheduling model is established according to the predicted wind power, considering the vehicle-to-grid (V2G) characteristics of EV, grid load fluctuations, wind curtailment capacity, EV charging costs, and grid losses. The global control aims to achieve overall energy balance and optimize the charging and discharging of EV in a time dimension under constrained conditions. Additionally, based on the total number of EV charging and discharging determined by the global level control, a spatial scheduling optimization is conducted for EV and wind power by the distribution network control, with the goal of minimizing network losses in the distribution network system. Finally, through simulation and comparison of four scenarios, the results demonstrate that the proposed method achieves synergistic optimization of wind power and EV. This paper provides an efficient solution for the optimized scheduling of large-scale EV connected to the predictable wind power grid.

Credibility Theory-Based Information Gap Decision Theory to Improve Robustness of Electricity Trading under Uncertainties

In the backdrop of the ongoing reforms within the electricity market and the escalating integration of renewable energy sources, power service providers encounter substantial trading risks stemming from the inherent uncertainties surrounding market prices and load demands. This paper endeavors to address these challenges by proposing a credibility theory-based information gap decision theory (CTbIGDT) to improve robustness of electricity trading under uncertainties. To begin, we establish credibility theory as a foundational risk assessment methodology for uncertain price and load, incorporating both necessity and randomness measures. Subsequently, we advance the concept by developing the CTbIGDT optimization model, grounded in the consideration of expected costs, with the primary aim of fortifying the robustness of electricity trading practices. The ensuing model is then transformed into an equivalent form and solved using established standard optimization techniques. To validate the efficacy and robustness of our proposed methodology, a case study is conducted utilizing a modified IEEE 33-node distribution network system. The results of this study serve to underscore the viability and potency of the CTbIGDT model in enhancing the effectiveness of electricity trading strategies in an uncertain environment.

Hybrid methodology-based energy management of microgrid with grid-isolated electric vehicle charging system in smart distribution network

Hybrid methodology-based energy management of microgrid with grid-isolated electric vehicle charging system in smart distribution network

A continuous‐time service network design and vehicle routing problem

AbstractThis paper considers the integrated planning of goods transportation through a multi‐echelon supply chain consisting of a nationwide network and regional distribution system. The previously studied Service Network Design and Routing Problem considered similar planning decisions, albeit with multiple restrictions regarding the transportation of goods that can eliminate the opportunities for transportation savings. It also does not explicitly model the opportunity to increase vehicle utilization by having vehicles serve multiple purposes within the supply chain. We propose a mathematical model of the problem we consider that is inspired by the operations of an industrial partner. We present an adaptation of the Dynamic Discretization Discovery algorithm to solve this problem and illustrate its computational effectiveness on instances derived from the operations of a retail distribution network in France. Finally, we illustrate the potential savings enabled by solving the proposed model.

Enhanced Non-Communication-Based Protection Coordination and Advanced Verification Method Using Fault Impedance in Networked Distribution Systems

In recent years, the networked distribution system (NDS), which is normally connected to the distribution line (DL), was actively studied as the topology of the future distribution system for reasons such as improving supply reliability, improving line utilization, and increasing the capacity of distribution generators (DGs). However, the NDS creates new issues in terms of protection coordination because of its bidirectional power flow and fault current flow. The issues associated with conventional protection schemes in the NDS include malfunction of protective devices due to bi-directional fault currents and failure of protection coordination due to communication failures between protective devices. When applying a conventional protection method in the NDS, the protection schemes become complicated, and there is a risk of protection coordination failure due to communication failure between protective devices. To solve this problem, this paper proposes an effective and innovative non-communication-based protection algorithm for protection coordination in the NDS. The proposed protection algorithm utilizes fault impedance characteristics, which allow not only determination of whether a fault occurred, but also the ability to identify the exact fault point. Therefore, the proposed method is expected to be sustainably utilized and contribute to developing protection schemes and devices in various system topologies and scenarios in the future. Additionally, this paper addresses the overall concept of hardware-in-the-loop simulation (HILS) and directly verifies the proposed protection algorithm using HILS. Therefore, this study establishes a sustainable foundation for future research on protection coordination using HILS.

A PSO-TVAC for optimal installation of multiple distributed generations in a radial distribution system

<span>The integration of distributed generations (DGs) into distribution system networks has seen a significant increase owing to the depletion of conventional energy resources and the growing power demand. However, a high penetration of DGs can adversely affect the stability of the distribution networks due to the intermittent nature of their generation capabilities. Hence, it is crucial to design DGs optimally to support grid voltage regulation and improve distribution networks performance. This study utilizes a particle swarm optimization (PSO) with time-varying acceleration coefficients (PSO-TVAC) technique to optimize the location and size of various distributed generation units while minimizing the total active power loss. The initial system power loss was determined using a distribution load flow analysis based on the backward-forward technique. The PSO-TVAC algorithm was then employed to identify the optimal placement and sizing of DGs within the standard IEEE 33-bus radial distribution network. To assess the proposed algorithm's effectiveness, photovoltaic (PV) and wind turbine (WT) were considered as the DGs. In comparison with other algorithms, PSO-TVAC achieved the lowest power loss, measuring 72.79 [kW] and 12.14 [kW] for <br /> 3-PV and 3-WT installations, respectively. Furthermore, the optimal installation of 3-PV and 3-WT improved the distribution system performance by 65.49% and 94.25%, respectively.</span>

Reliability Comparison of Rural & Urban LVDS Networks with Corresponding HVDS Networks Including Substation Reliability

This paper mainly determines the comparison of reliability of an existing rural area & urban area LVDS (low voltage distribution system) with their respective proposed high voltage distribution system (HVDS) and also including their 33/11 kV Substation. Ring main substation and single bus bar substation configuration are considered for urban and rural distribution systems respectively. The reliability of ring bus substation used in urban area is more as compared to single bus substation used in rural area. The load point reliability indices are calculated considering both substation reliability indices and radial feeder indices. The substation failure rate is calculated by considering overlapping outages approach and whereas the radial feeder indices are calculated by using cut set approach. Further, the LVDS Network is converted into the HVDS Network by replacing a high rating distribution transformer (DTR) supplying to a group of customers with Large in number with multiple small rating distribution transformers near to consumer terminals with less number of customers in each group. This conversion leads to Minimum length of LT Lines in HVDS Which results in improving voltage profile, reliability and efficiency. In this paper the disconnecting switches and alternative supply are also considered on both LVDS and HVDS Networks in the calculation of the reliability of to assess the reliability of the radial distribution system (FMEA)Failure mode effect analysis is used. This study uses a LVDS and HVDS system, and uses an alternative power source and disconnectors, to determine reliability indices of the rural area network and urban area network distribution system. In this paper the important distribution reliability indices to reduce system average interruption durations (SAIDI), Energy Not Supplied (ENS) and ASAI for LVDS and corresponding HVDS are calculated. The research idea is proposed on a Indian practical networks.

A Study on a Communication-Based Algorithm to Improve Protection Coordination under High-Impedance Fault in Networked Distribution Systems

The rising demand for stable power supply in distribution systems has increased the importance of reliable supply. Thus, a networked distribution system (NDS) linked with individual lines is being adopted, gradually replacing the radial distribution system (RDS) currently applied to most distribution systems. Implementing the NDS can lead to various improvements in factors such as line utilization rate, acceptance rates of distributed power, and terminal voltages, while mitigating line losses. However, compared with the RDS, the NDS can experience bidirectional fault currents owing to its interconnected lines, thereby hindering protection coordination, which must be addressed before the NDS can be implemented in real-world power systems. Due to the characteristics of NDS, the reverse fault current is relatively small. However, this phenomenon becomes more severe when the high impedance fault (HIF) occurs. In this paper, the malfunction of protective devices during the HIF is directly verified and analyzed in the NDS. As a result, when the HIF occurs, the issue of the reverse protective device malfunctioning worsens because of a reduction in fault current and a failure in direction detection. To solve this issue, this work proposes a communication-based protection algorithm. Through the comparative verification of the proposed algorithm and the conventional protection method, protection coordination can be secured in the case of an HIF without new devices. It must be highlighted that the proposed method does not affect the settings of the protective device and provides a cost-effective and efficient solution since this algorithm is added independently to the existing relay.

Operating inlet pressure head assessment for multi-outlet submain manifolds in a low-pressurized water distribution network system

Abstract Multi-outlet pipes can be used to distribute and collect fluids and have applications in various engineering fields, especially in the water supply system. The hydraulic design of a submain unit pipeline with multiple outlets is a very important concern for the proper hydraulic performance of irrigation water distribution systems. The operating inlet pressure head, H0I, is a main hydraulic component for the proper hydraulically efficient design and evaluation of pressure head distribution along the line. The energy-gradient ratio (EGR) approach is a useful tool to identify first which type of pressure profile occurs for a given uniform design slope with other hydraulic variables initially known and then, comprehensively evaluate its definite hydraulic characteristics along the line. Knowing the hydraulic properties of any type of pressure profile regarded enables the design engineer to evaluate pressure parameters through the line sections in a simple way. The procedure is simplified by regarding the localized head loss along the pipe but neglecting the change in kinetic head. The present analytical technique performs sufficiently accurately in comparison with the computer-aided software design technique, for all performed simulations.

Optical fiber sensor with a bi-cavity ring-down differential technology for robot-finger distributed systems

Contemporary intelligent robots typically necessitate the implementation of a distributed sensing network system within their digits to execute a range of intricate tasks collaboratively. In this investigation, we have introduced a novel fiber sensor founded on an enhanced fiber-loop ring-down spectral technology. This sensor employs double differential ring-down cavities to mitigate prevalent sources of interference, such as temperature and humidity. Consequently, it exhibits a robust linear response with remarkable sensitivity, quantified at 105.2 ns/N for force measurement and 53.2 ns/mm for displacement measurement, as validated by experimental outcomes. Furthermore, the sensor boasts a compact and diminutive sensing structure that can be effortlessly integrated into the robotic finger casing. Of utmost significance, it facilitates a cost-effective time-division multiplexing system for distributed measurements. Considering these distinctive advantages, this sensor lends itself to the establishment of a practical robot-finger distributed network system, characterized by superior performance attributes, encompassing high precision (up to 19 μm for contact detection and 0.0095 N for grasping and other manipulations), relatively modest expenses, and versatile applicability across a broad spectrum of scenarios, in stark contrast to the presently prevalent systems. In light of these noteworthy merits, the developed sensor exhibits tremendous potential for integration into robotics applications.

Energy Storage‐Reactive Power Optimal Configuration for High Proportion New Energy Distribution Network Considering Voltage Quality and Flexibility

The increasing penetration rate of distributed energy brings more complex problems of voltage quality, safety and stability to the distribution network. A single optimal configuration of reactive power or energy storage is difficult to meet the increasingly diversified needs of modern power grids. This paper proposes a configuration strategy combining energy storage and reactive power to meet the needs of new energy distribution networks in terms of active power regulation and reactive power compensation, and to achieve tradeoff optimization in flexibility, voltage quality and economy, so as to adapt to the influence of new energy with different permeability. Firstly, the safety and stability evaluation system of distribution network is established with the target of flexibility demand and reactive power demand. Secondly, considering the coupling of planning layer and operation layer, a two‐layer model of energy‐reactive power optimization is established. After that, the gray wolf algorithm is used to solve the model, which enhances the global space exploration ability and reduces the possibility of falling into the local optimal. Finally, the improved IEEE33 node power distribution system is used for simulation test to verify the rationality and effectiveness of this scheme. The simulation results show that the scheme proposed in this paper can effectively improve the economy, security and stability of the distribution network, and can obtain an optimal configuration scheme with multi‐objective considerations under different new energy penetration rates. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A New Control Strategy of Hybrid Reactive Power Compensation System in Distribution Network

Reactive power compensation is an important measure to improve the power quality of distribution networks, especially with the increasing connection of distribution transformers, heavy industrial electrical equipment, and asynchronous motors, which generate a large amount of reactive power demand. Traditional reactive power compensation devices, such as fixed capacitors (FC) and thyristor switched capacitors (TSC), have some drawbacks, such as low response speed, harmonic generation, and switching shock. A static synchronous compensator (STATCOM) is a flexible AC transmission system (FACTS) device that can provide fast and continuous reactive power compensation, but it also has some limitations, such as high cost, large capacity requirement, and low utilization rate. Therefore, hybrid reactive power compensation systems that combine FC or TSC with STATCOM have attracted much attention in recent years. Many researchers have proposed and studied different topologies and control methods of hybrid systems to overcome the disadvantages of single devices and achieve better performance. However, most of the existing hybrid systems are designed for low or medium-voltage distribution networks, and their performance under high-voltage distribution networks is still unclear. Moreover, the coordination control strategy of the hybrid system and its subsystems is also a key issue that affects the effectiveness and efficiency of reactive power compensation. In view of this, this paper aims to propose a TSC+STATCOM hybrid reactive power compensation system for high-voltage distribution networks, which optimizes the shortcomings of traditional reactive power compensation devices. The system uses the synergistic effect of TSC and STATCOM to achieve large-scale static reactive power and small-scale dynamic reactive power compensation and adopts a switching strategy based on an expert decision system. This paper introduces the working principle of each subsystem of the hybrid reactive power compensation system in detail and builds a simulation model of the hybrid reactive power compensation system under a high voltage distribution network on Matlab/Simulink platform. The simulation results verify the feasibility and excellent performance of the system control method in reactive power compensation and improving power quality.

Optimization of logistics supply chain management model on consumer purchase anxiety disorder

BackgroundAnxiety refers to the intense, excessive, and persistent anxiety and fear in daily life, which will peak in a few minutes. Especially in online shopping, patients with anxiety will aggravate their anxiety because of the slow delivery of the traditional logistics supply chain management model. To reduce consumers’ anxiety, the network distribution system of logistics supply chain management mode is optimized.Subjects and MethodsThis study divided 200 patients with anxiety disorder in a city into a control group and an experimental group. In the experimental group, 100 patients used the optimized logistics supply chain management mode for online shopping. In contrast, in the control group, 100 patients used the traditional logistics supply chain management mode for online shopping. The study also used the self-rating anxiety scale (SAS) for psychological measurement and compared the SAS scores of the two groups of consumers for two months.ResultsThe data were analyzed by SPSS23.0. The SAS score of the experimental group was (1.63±0.23), and that of the control group was (1.81±0.59). The SAS scores of patients in the experimental group were better than those in the control group, and there were apparent differences between the two groups (P < 0.05).ConclusionsResearch on the choice of logistics supply chain management mode for online shopping optimizing its network distribution system can effectively shorten the online shopping distribution time and reduce consumers’ purchase anxiety.

The Joint Application of Photovoltaic Generation and Distributed or Concentrated Energy Storage Systems in A Low Voltage Distribution Network: A Case Study

The Joint Application of Photovoltaic Generation and Distributed or Concentrated Energy Storage Systems in A Low Voltage Distribution Network: A Case Study

Optimal planning of distributed generation and energy storage systems in DC distribution networks with application of category-based multi-objective algorithm

The strategic positioning and appropriate sizing of Distributed Generation (DG) and Battery Energy Storage Systems (BESS) within a DC delivery network are crucial factors that influence its economic feasibility and dependable performance. To tackle this vital aspect, we have formulated a multi-objective optimization model aimed at determining the most advantageous locations and capacities for DG and BESS. Our approach establishes a framework for multi-objective optimization that systematically addresses all objectives, minimizing bias towards any specific set of objectives and enhancing overall efficiency. Furthermore, from a variety of collective objectives we introduce an improved Multi-Objective Particle Swarm Optimizer (IMOPSO) tailored to produce and choose Pareto best solutions. To identify the best placement and sizing options for DG and BESS among the Pareto optimal solutions, we apply the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) strategy, integrating an information entropy method. We have conducted simulations using the 33-bus DC distribution grid of IEEE to validate the practical benefits of our suggested methodology.

Resilience Enhancement with Transportable Storage Systems and Repair Crews in Coupled Transportation and Distribution Networks

The significance of resilience within power system infrastructures has been progressively acknowledged. To address this challenge, this paper introduces an innovative framework to enhance distribution network (DN) resilience by incorporating transportable storage systems (TSSs). To do so, we take into account the interconnection between the DN and the transportation network (TN) to optimize the trajectory planning of TSSs. To account for real-world features, the traffic flow of TN is modeled according to traffic counter cameras of Sioux Falls city. In addition, the effects of blocked roads on TSSs' movements through microgrids (MGs), and clearing operation of obstructions by repair crews are considered as these factors have a great impact on system operational cost. Further, an optimal reconfiguration program is proposed to add more flexibility to the system. The developed model is formulated as mixed-integer linear programming (MILP) and various case studies are presented including analyzing TSSs and repair crews’ operations, both individually and concurrently. Different case studies reveal the positive impact of TSSs, reducing the total cost of the system by approximately 13.11%. In post-event, blocked roads directly increase the operation costs by 17.02%; however, repair crews' cooperation with TSSs, achieved a remarkable 12.75% reduction in operation costs.

A fault segment location method for distribution networks based on spiking neural P systems and Bayesian estimation

With the increasing scale of distribution networks and the mass access of distributed generation, traditional centralized fault location methods can no longer meet the performance requirements of speed and high accuracy. Therefore, this paper proposes a fault segment location method based on spiking neural P systems and Bayesian estimation for distribution networks with distributed generation. First, the distribution network system topology is decoupled into single-branch networks. A spiking neural P system with excitatory and inhibitory synapses is then proposed to model the suspected faulty segment, and its matrix reasoning algorithm is executed to obtain a preliminary set of location results. Finally, the Bayesian estimation and contradiction principle are applied to verify and correct the initial results to obtain the final location results. Simulation results based on the IEEE 33-node system validate the feasibility and effectiveness of the proposed method.