Conventional Distribution Network Research Articles

Enhanced frequency control of a hybrid microgrid using RANFIS for partially shaded photovoltaic systems under uncertainties

Nowadays environmental concerns and fossil fuel limitations, as well as economic benefits and technical issues such as reliability lead conventional distribution networks to smart microgrids, where the renewable energy resources are merged with the grids. Nevertheless, the systems face new challenges due to the intermittent nature and uncertainties in the distributed generations, which cause frequency fluctuations in the microgrid. The photovoltaic cells are the main part of the contemporary microgrids. Although the photovoltaic (PV) systems depend on solar irradiance, and temperature and are affected by the partial shading phenomenon they could contribute to improving the microgrid frequency stability with a proper control scheme. In this paper, the frequency control strategy is designed for a hybrid stand-alone microgrid, which is robust against load disturbances, variations in weather conditions, and uncertainties in the microgrid parameters. The proposed intelligent control scheme relies on the Recurrent Adaptive Neuro Fuzzy Inference System (RANFIS). The Whale Optimization Algorithm (WOA) is employed to optimize the RANFIS controller structure and generate the parameters of membership functions. In this multi-objective optimization, the objectives are settling time (ST), overshoot (Osh), and Integral Square Error (ISE). The simulation results verify the high robustness and performance of the proposed RANFIS controller, compared to other controllers, during various operational circumstances, as well as the sporadic behavior of renewable energy resources (RES) such as fluctuations in solar radiation and certain uncertainties in the microgrid parameters.

A new data-driven distributed power grid load storage resource-wide area voltage self-optimization control method for distribution system

Abstract Different from the conventional energy distribution network, which solely relies on energy distribution, the novel distribution system gradually exhibits a complex and interconnected form of various resources, such as source network load storage. These resources possess characteristics of “multi-point, wide area, and small amount” distribution. Investigating the potential for wide-area voltage regulation by using distributed resources like renewable energy power generation, distributed energy storage, and flexible loads is crucial for constructing a highly integrated source network load storage in the new type of distribution system. This paper proposes a novel data-driven method for optimizing control of wide-area voltage through distributed power network load storage resources. By comprehensively and cooperatively controlling renewable energy power generation, energy storage systems, and flexible loads, this approach enhances the quality of wide-area voltage in the distribution network while ensuring optimal utilization of energy storage capacity and minimizing network losses. The effectiveness and advanced nature of this method are demonstrated by applying it to an urban distribution network example. Compared to traditional voltage regulation methods, this approach aligns better with the requirements for voltage regulation in the new type of distribution network.

Optimal hybrid resonant current controller for microgrids connected to an unbalanced IEEE test distribution network

Microgrids (MGs) based on renewable energies have emerged as a proficient strategy for tackling power quality issues in conventional distribution networks. Nonetheless, MG systems require a suitable control scheme to supply energy optimally towards the electrical grid. This paper presents an innovative framework for designing hybrid Proportional-Resonant (PR) controllers with Linear Quadratic Regulators (LQR), PR+LQR, which merge relevant properties of PR and LQR controllers. This method simultaneously determines the MG control parameters and the current unbalanced factor generated at the distribution network. We select the traditional IEEE 13-bus test feeder network and place two MGs at strategic locations to validate our approach. Moreover, we use the Grey Wolf Optimizer (GWO) to find control parameters through a reliable fitness function that leads to high-performance microgrids. Finally, we conceive several tests to assess the efficacy of GWO for tuning the hybrid controller and compare the resulting data across distinct realistic operation conditions representing power quality events. So, we choose four case studies considering different renewable energy penetration indexes and power factors and evaluate the effects of the MGs over the distribution grid. We also compare the proposed hybrid PR+LQR controller against closely-related alternatives from the literature and validate its robustness and stability through the disk margin approach and the Nyquist criterion. Our numerical simulations prove that hybrid controllers driven by GWO are highly reliable strategies, yielding an average unbalanced current reduction of 30.03%.

System modeling of the impact of multiple capacitor coupled substations located at different proximities on a transmission network

Electricity plays a vital role in the economy of any nation, and its availability has transformed from being a luxury to being an essential requirement. However, the implementation of conventional distribution networks in sparsely populated rural areas is often deemed economically impractical. Consequently, the exploration of alternative technologies for rural electrification becomes imperative. One such technology is the Capacitor Coupled Substation (CCS), which taps electrical power from high-voltage lines through coupling capacitors. Given that capacitors can introduce interference in an electrical system, the deployment of a CCS necessitates consideration to minimize these network disturbances. This paper modelled and analyzed the impact of multiple CCSs on the electrical transmission network, with a specific focus on the impact on the transmission line voltage when multiple CCSs are located at different proximity to one another. A typical electrical transmission network with fixed supply voltage represented as 230kVac and downstream parameters with a 230kVac and 100 kW load was selected. A system model comprising three CCSs, located at known proximities from one another, was developed using MATLAB/Simulink to simulate the network's response when one or more CCS units are connected or disconnected from the electrical transmission network. Three prototypes were also constructed to represent real-world electrical systems with different loads. The model simulation was executed while connecting and disconnecting one or more CCS at a time and at different proximities from one another within the electrical transmission network. The same procedure was repeated on the prototypes where they were connected and disconnected from the selected network. The proximity to one another was represented by different resistances which represented the electrical transmission lines between the different locations of each CCS on the electrical network. The obtained test results were subjected to comparison across three platforms: the MATLAB/Simulink model, physical prototype testing using a multimeter, and digital testing using an oscilloscope. The results showed negligible disruptions on the supply side and downstream side of the transmission network. The primary goal of this research was to provide valuable insights into the potential application of CCS technology in rural electrification by examining its impact on the transmission network. Further analysis is recommended to understand the impact of each critical component within a CCS.Capacitor Coupled Substation; Rural Electrification; System Modeling; Multiple CCS

Power quality interval grading evaluation method of AC/DC distribution network considering source-load weighting and voltage coupling

In the context of the ‘dual carbon’ goal, the integration of renewable energy sources has a significant impact on distribution systems, while the substantial integration of DC loads and photovoltaic power has led to a progressive transition of conventional distribution networks towards hybrid AC-DC distribution networks in the field of electrical engineering. However, this shift has brought about more formidable power quality challenges within the power industry. To address these emerging power quality issues, we propose a novel power quality interval grading evaluation method for AC/DC distribution networks considering source-load weighting and voltage coupling. Firstly, the voltage acquisition data is meticulously decoupled to disentangle the interdependencies. Secondly, the power quality evaluation system of the AC/DC distribution network is established. Considering the influence of different access source-load types on each node, the subjective weight is determined by source load weighted two-tuple linguistic analytic hierarchy process (AHP), the objective weight is determined by the entropy weight method, and the idea of using game equilibrium algorithm to obtain comprehensive weight to balance the error of single weight on evaluation result is put forward. Then, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) of interval number improvement is used to classify and evaluate the power quality index to make up for the shortcomings of the single-point sampling method. Finally, a more accurate and comprehensive power quality evaluation result is obtained based on a practical example.

Impact of Superconductor Technologies on Network Design and Energy Cost- a Case Study in Libya

Several studies and investigations haveattempted to introduce a new design for the conventionaldistribution networks. This proposed design aims to offer a reduction in substation installation cost and in power losses by eliminating some voltage levels in networks. Sine, this is difficult to achieve with conventional distribution networks, when the conventional cables and transformers are used, where the impedance of conventional equipment is high. Due to High-Temperature Superconductor (HTS) materials provide extremely low impedance to AC when cooled to the boiling point of liquid nitrogen (77K), the interest in using HTS materials to produce power cables and transformers is increased. The present paper investigates the practical impacts of installing HTS cables and transformers and seeks to introduce a future network design which leads to the best implementation for superconducting networks, thus, a drop in the substation installation cost and energy losses cost by eliminating some voltage levels in the traditional networks.

Optimal Switch Insertion for Power Loss Reduction and Reliability Enhancement in the Nigeria Conventional Distribution Networks: A Case Study

This paper seeks to analyze the potentials of optimal switch insertion and relocation of the existing ones in the Nigeria conventional distribution network for reliability enhancement and power loss minimization. Maximizing customers’ satisfaction and enhancement of service reliability of the distribution network isa critical thing to utility and how to achieve it is also a major concern? Optimal switch insertion can enhance the network operation, minimize power losses in the lines, increase service restoration to blackout areas and improve the electric power supply to customers in the distribution network and increase the system reliability. The impact of optimal insertion of sectionalizing switches and optimal relocation of the existing ones for reliability enhancement and power loss reduction in real-time distribution network has been investigated. Additionally, the research examined the history of frequent power interruptions in the network and their cost implication on the system and customers alike, and as well as the benefits of eliminating frequent outages in the Nigeria distribution networks as a case study. Also, feeder ranking based on reliability indices, customer damage function (CDF), capital investment and their correlations were analyzed and established. Conclusively, the results depicted that the reliability of the network can be affected by the number of sectionalizing switches introduced by an optimal relocation of the existing ones and their locations as well as its capacity of power loss reduction in the network.

The Detection of False Data Injection Attack for Cyber–Physical Power Systems Considering a Multi-Attack Mode

Amidst the evolving communication technology landscape, conventional distribution networks have gradually metamorphosed into cyber–physical power systems (CPPSs). Within this transformative milieu, the cyber infrastructure not only bolsters grid security but also introduces a novel security peril—the false data injection attack (FDIA). Owing to the variable knowledge held by cyber assailants regarding the system’s network structure, current achievements exhibit deficiencies in accommodating the detection of FDIA across diverse attacker profiles. To address the historical data imbalances encountered during practical FDIA detection, we propose a dataset balancing model based on generating adversarial network-gated recurrent units (GAN-GRU) in conjunction with an FDIA detection model based on the Transformer neural network. Harnessing the temporal data extraction capabilities of gated recurrent units, we construct a GRU neural network system as the GAN’s generator and discriminator, aimed at data balance. After preprocessing, the balanced data are fed into the Transformer neural network for training and output classification to discern distinct FDIA attack types. This model enables precise classification amidst varying FDIA scenarios. Validation involves testing the model on load data from the IEEE 118-bus system and affirming its high accuracy and effectiveness in detecting power systems after multiple attacks.

An approach to disparage the blindness of backup protection in grid connected renewable energy sources system by inducing artificial fault current

The renewable energy sources based distributed generation is increasingly penetrating into conventional distribution network . Aside from the technical and economical benefits, distributed generation may incapacitate the sensitivity of backup protection devices , which may face partial blindness in grid-connected, even full blindness in islanded mode of operation and during high impedance faults. This paper proposes a novel stratagem to completely plummet the blindness of backup relay by inducing the artificial fault current. A blindness severity index is developed to induce artificial fault current in a controlled manner according to blindness severity. Two methods are proposed. First, the OCR vulnerable to blindness is provided with an auxiliary current transformer, whose output is tuned in conjunction with blindness severity index and merged with main current transformer’s output to modulate its secondary current responsible for sensitivity. Second, the microprocessor based relay is used and the time current characteristics is modified by augmenting a new variable named as artificial fault current factor to scale the fault current. As, the current is increased by the TCC modification and no external equipment is added here, so named as AFC. To assure that the AFC is induced only in fault event and to prevent mal-functioning of OCR during normal operation, a simple logic is designed using AND gates to fend off trip signal to circuit breaker. The proposed protection scheme is evaluated on typical distribution feeder in Tianjin, China and IEEE-34 standard test benchmark and results show that the blindness of backup PDs is dwindled in a proficient manner.

Demand-Side Management of Self-Sustained Droop Based Standalone Microgrid Using Conservation Voltage Reduction Strategy

Self-sustained microgrid (MG) carries the potential to replicate a conventional grid network with a smooth and robust control scheme to generate and disseminate power with the integration of diverse renewable sources by employing the voltage source inverter (VSI). The power generation capability is the primary function of VSI in an inverter-based distributed generation (DG). In addition, it is also operated to perform the task of demand-side management with the utilization of the conservation voltage reduction (CVR) strategy. In a conventional distribution network, the CVR strategy is exploited by voltage deduction within permissible range with the support of open-loop schemes, such as tap changers, capacitors, or close-loop schemes, such as supervisory control and data acquisition system. However, the CVR's applicability in a standalone MG is still a viable approach to be delved into and hence, this article intends to employ CVR by utilizing the conventional P-f droop and V-I droop principle in inverter-based DG. The proposed strategy produces voltage compensation according to the degree of voltage or frequency variation and therefore, the degree of voltage reduction is not fixed but it varies with the disturbance. The proposed control mechanism relies on the deviation of the voltage generated by the V-I droop and frequency output provided by the P-f droop during the overloading and peak demand condition. In addition to it, a control methodology is devised to check the coordination between CVR and load shedding strategy to shed load during overloading conditions. The performance testing of the proposed control methodology is being validated through real-time Opal-RT device.

Optimal Placement of Distributed Generation Units for Microgrid Planning in Distribution Networks

Due to increasing penetration of renewable distributed generation (DG), conventional distribution networks have been gradually transforming into their active form, where microgrids may serve as fundamental building blocks. As the primary step towards microgrid planning, optimal DGs placement and sizing can reduce the total energy losses by localizing power supply to loads. In this paper, a DG optimal placement method by minimizing the total energy losses is proposed, where the planning is formulated as a non-linear programming (NLP) problem. AC optimal power flow (OPF) is used to solve this planning problem by considering operational constraints and uncertainties in load and renewable power generation of the network. IEEE 33-bus test system and a real 404-bus distribution system operated by Saskatoon Light and Power in Saskatoon, Canada are used to validate the proposed method. The proposed method also shows superior performance compared to existing methods.

Low Computational Burden Adaptive Overcurrent Protection for Active Distribution Networks

Conventional distribution networks have evolved into active distribution networks due to the high penetration of distributed energy resources. These new networks have several protection issues; some are related to the high fault and load current variations due to the various operating conditions. This situation is faced by adaptive protection development, as proposed in this study, where variations among active distribution network operating conditions are considered to estimate the adaptive pickup current. This is used to estimate the overcurrent relay’s time dial setting, avoiding miscoordination. The proposed protection approach uses fast calculations and local measurements; consequently, a low computational burden is required to update the adaptive relay parameters for each operating condition without using communication infrastructure. The obtained results in the IEEE 34-nodes test feeder demonstrate the advantages of the proposed approach, accomplishing the coordinating time interval for phase and ground faults. These results show a high performance of primary and backup protection at different operating conditions of the proposed test system compared to the performance of the conventional protection approach. The proposed approach’s high performance, low computational burden, and communicationless characteristics make it suitable for immediate real-field implementation.

Coordinated Cloud-Edge Anomaly Identification for Active Distribution Networks

The extensive integration of distributed energy resources transforms the conventional power distribution network into a complex and tightly-coupled cyber-physical system denoted as active distribution network (ADN). In this paper, a data-driven anomaly identification method based on the cloud-edge computing architecture is proposed to reduce the complicated risk of ADN operations. Especially, the proposed method would serve as a widely applicable and efficient line of defense against either cyber or physical anomalies. On one hand, a hierarchical data flow scheme is designed to balance the timeliness and economical requirements of anomaly identification by taking advantage of coordinated cloud-edge computing. On the other hand, an integrated algorithm is proposed on the basis of the proposed data flow architecture in order to identify anomalies with satisfactory robustness and accuracy, even under complex cyber-physical conditions. Results of numerical experiments have validated the computational superiority of the proposed method over the state-of-the-art by simulating a variety of physical faults and cyber attacks.

Current Trends in Electric Vehicle Charging Infrastructure; Opportunities and Challenges in Wireless Charging Integration

Nowadays, the imperative need for the reduction of Greenhouse Gas (GHG) emissions leads to the wider adoption of environmentally friendly transportation means. As a result, various policies underpinning the Electric Vehicle (EV) deployment are legislated globally, and several technical advances contributing to the electrification of the transportation sector are pursued. In this paper, a comprehensive overview of the current status of the infrastructure utilized for the realization of both conductive and contactless (wireless) charging of an EV battery is conducted. Furthermore, the issue of EV integration in conventional distribution networks, as well as in future power system architectures, is discussed in detail. Particular focus is given to wireless (i.e., inductive) charging. A detailed presentation of the respective standards and charging levels, as well as the magnetic couplers and the compensation network configurations, is carried out. Moreover, innovative concepts such as dynamic and quasi-dynamic wireless charging, as well as future challenges and opportunities, are presented and discussed. Finally, smart control and communication techniques applicable to EV charging are presented in the context of the future Internet of Energy (IoE) concept.

Fundamental factors influencing bus coherency in distribution networks with distributed energy resources

With the participation of distributed energy resources (DERs) in inertia emulation, voltage control and primary frequency response, distinct angle and voltage dynamics are introduced in a conventional distribution network. These additional low-frequency dynamics emanating from a pre-dominantly resistive distribution network influence the mode properties of system oscillations uniquely. For better control and partitioning of active distribution network during emergency conditions coherent participation of DERs in local and inter-area modes need to be evaluated. In this work, fundamental factors affecting the bus coherency of distribution system are analyzed. It introduces a concept of coherency duality between pre-dominantly resistive and inductive distribution networks along with unique effect of source and control interactions by DERs. The work discovers pre-dominance of voltage based coherency criteria for active power flow control/islanding in resistive sub-networks and angle based criteria for inductive sub-networks, due to the reverse relation between state and power variables. Dynamic coherency changes inflicted by DER variabilities like different control and source interactions, increased penetration level, change in the spatial distribution of DERs, and dynamic loading are presented in the work. The proposition is tested for modified IEEE-39 bus systems with 33 bus 132/33/11/0.4 kV and 2182 bus 20/0.4 kV distribution networks in DigSILENT/PowerFactory.

Smart Distribution Mechanisms—Part I: From the Perspectives of Planning

To enhance the reliability and resilience of power systems and achieve reliable delivery of power to end users, smart distribution networks (SDNs) play a vital role. The conventional distribution network is transforming into an active one by incorporating a higher degree of automation. Replacing the traditional absence of manual actions, energy delivery is becoming increasingly dependent on intelligent active system management. As an emerging grid modernization concept, the smart grid addresses a wide range of economic and environmental concerns, especially by integrating a wide range of active technologies at distribution level. At the same time, these active technologies are causing a slew of technological problems in terms of power quality and stability. The development of such strategies and approaches that can improve SDN infrastructure in terms of planning, operation, and control has always been essential. As a result, a substantial number of studies have been conducted in these areas over the last 10–15 years. The current literature lacks a combined systematic analysis of the planning, operation, and control of SDN technologies. This paper conducts a systematic survey of the state-of-the-art advancements in SDN planning, operation, and control over the last 10 years. The reviewed literature is structured so that each SDN technology is discussed sequentially from the viewpoints of planning, operation, and then control. A comprehensive analysis of practical SND concepts across the globe is also presented in later sections. The key constraints and future research opportunities in the existing literature are discussed in the final part. This review specifically assists readers in comprehending current trends in SDN planning, operation, and control, as well as identifying the need for further research to contribute to the field.

Multiport AC-AC-DC Converter for SNOP With One Medium-Frequency Transformer

With the access of increased renewable energy sources, the conventional AC distribution network is hard to flexibly adjust the line voltage and power flow. Therefore, the soft normally open point (SNOP) is applied to increase the flexibility of AC distribution network. The existing converters for SNOP use many submodules (SMs) and passive components, which have the poor economy. On this basis, a multiport AC-AC-DC converter for SNOP with one medium-frequency transformer (MFT) is proposed in this paper. The proposed multiport AC-AC-DC converter is based on the back-to-back (BTB) cascaded H-bridge (CHB) converter structure, and uses several LC resonant circuits and one MFT to replace the multiple DC-DC converters in the existing BTB CHB converters. Therefore, many SMs and passive components can be saved. Moreover, the voltages at multiple AC and DC ports of proposed multiport AC-AC-DC converter are completely decoupled, and the multiple AC and DC systems can be adjusted independently. The detailed circuit structure, control principle and design procedure of multiport AC-AC-DC converter are introduced in this paper. Finally, the simulation and experimental results verify the effectiveness of multiport AC-AC-DC converter.

Application of Distributed Ledger Technology in Distribution Networks

In the transition to a society with net-zero carbon emissions, high penetration of distributed renewable power generation and large-scale electrification of transportation and heat are driving the conventional distribution network operators (DNOs) to evolve into distribution system operators (DSOs) that manage distribution networks in a more active and flexible way. As a radical decentralized data management technology, distributed ledger technology (DLT) has the potential to support a trustworthy digital infrastructure facilitating the DNO–DSO transition. Based on a comprehensive review of worldwide research and practice, as well as the engagement of relevant industrial experts, the application of DLT in distribution networks is identified and analyzed in this article. The DLT features and DSO needs are first summarized, and the mapping relationship between them is identified. Detailed DSO functions are identified and classified into five categories (i.e., “planning,” “operation,” “market,” “asset,” and “connection”) with the potential of applying DLT to various DSO functions assessed. Finally, the development of seven key DSO functions with high DLT potential is analyzed and discussed from the technical, legal, and social perspectives, including peer-to-peer energy trading, flexibility market facilitation, electric vehicle charging, network pricing, distributed generation register, data access, and investment planning.

Supplementary Feedforward Voltage Control in a Reconfigurable Distribution Network using Robust Optimization

Network reconfiguration (NR) has attracted much attention due to its ability to convert conventional distribution networks (DNs) into self-healing grids. This paper proposes a new strategy for real-time voltage regulation (VR) in a reconfigurable DN, whereby optimal feedforward control of distributed generators (DGs) is achieved in coordination with the operation of line switches (SWs). This enables preemptive compensation of upcoming deviations in DN voltages resulting from NR-aided load restoration. A robust optimization problem is formulated using a dynamic analytical model of NR to design the feedforward voltage controllers (FVCs) that minimize voltage deviations with respect to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> norm. Errors in the estimates of DG modeling parameters and load demands are reflected in the design of optimal FVCs via polytopic uncertainty modeling. Small-signal analysis and case studies are conducted, verifying the effectiveness and robustness of the optimal FVCs in improving real-time VR when NR is activated for load restoration. The performance of the proposed FVCs is confirmed under various conditions of a self-healing DN,characterized by network islanding and size, parameter errors, SW operations, and communication time delays.

Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach

The planning and operation of distribution systems have significantly changed due to the extensive osmosis of ICT (information and communication technologies) into power systems. Load growth, together with increased power quality expectations by the customers, has transformed the conventional distribution network to active distribution network (ADN), with penetration of distributed energy resources (DERs). This has imposed the necessity to analyze resilient performance of ADN subjected to the boon of ICT for enhanced situational awareness (SA). This paper focuses on a detailed multi-level hierarchy framework using linguistic scale based multi-criteria decision-making (MCDM) approach for SA oriented resilience level estimation of ADN, considering different high impact low frequency (HILF) events. The rapidly changing environmental conditions and ambiguity in interaction of network parameters lead to non-deterministic resilience (NDR), thus, affecting the operational resilience of ADN on a daily basis. To analyze the uncertain ADN availability due to NDR, hybrid MCDM-dynamic Bayesian network (DBN) approach is used. For better decision-making, the operational performance of ADN, to withstand critical loads due to NDR is analyzed in terms of load not served (LNS) index. The proposed framework is tested on IEEE 33-bus distribution network.