Large-scale Distributed Generation Research Articles

Multi-objective Reactive Power Optimization of a Distribution Network based on Improved Quantum-behaved Particle Swarm Optimization

Background: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation (RDG) access. Objective: To address the problems caused by the connection of RDG, an RPO model and an improved quantum-behaved particle swarm optimization (IQPSO) algorithm are proposed. Method: In this study, a dynamic S-type function is proposed as the objective function of the minimum active power loss, whereas an exponential function is proposed as the objective function of the minimum voltage deviation to establish an RPO objective function. The operating cost of distribution is considered as the third objective function. To address the RPO problem, a QPSO algorithm based on the ε-greedy strategy is proposed in this paper. ModifiedIEEE33 bus and IEEE69 bus systems were used to evaluate the proposed RPO method in simulations. Results: The simulation results reveal that the IQPSO algorithm obtains a better solution, and the proposed RPO model can considerably reduce active power loss, node voltage deviation, and distribution network operating costs. Conclusion: The RPO model and IQPSO algorithm proposed in this study provide a highperformance method to analyze and optimize reactive power management in distribution network.

Temporal Scenarios-based Assessment of Maximum Hosting Capacity of Renewable Generation in Distribution Systems Considering ANM Techniques

Abstract Incorporating large-scale renewable distributed generation (RDG) into the power grid introduces significant challenges associated with the indeterminacy of the power system, significantly impacting the comprehensive integration and efficient utilization of the distribution network. This underscores the imperative to investigate scientific evaluation methods and mechanisms for enhancing the RDG absorptive capacity within the distribution network. In light of the stochastic and temporal characteristics inherent to RDG, a novel approach for assessing the RDG hosting capacity within distribution networks is proposed, taking temporal scenarios into account. This method optimizes the RDG output probability distribution model based on its temporal fluctuation change rule, and constructs RDG temporal scenario model by using scenario reduction technology. Subsequently, a temporal scenarios-based RDG hosting capacity assessment model is established, taking into account active network management (ANM) techniques. The effectiveness of the proposed methodology is substantiated through simulation results conducted on a modified IEEE 33-bus system.

Probability and Severity Based Overvoltage Risk Analysis Considering Large-Scale DG Access

Abstract With the rapid increase of distributed generation (DG) in the distribution network (DN), the analysis of DG maximum bearing capacity (DGMBC) is paid more attention. However, the existing methods can not precisely simulate the overvoltage risk concerning occurrence probability and severity. To this end, the overvoltage scenario classification method and overvoltage severity coefficient correction method are proposed in this paper, which can effectively reflect the real overvoltage risk in DN. The IEEE 33-bus test feeder is used to compare the calculation results of overvoltage risk with other methods.

Control and Protection of Medium Voltage Distribution Network Based on Unified Power Flow Controller

The integration of diverse load types, such as large-scale distributed generators and charging stations, presents considerable challenges to distribution networks. The Unified Power Flow Controller (UPFC) provides multiple benefits, including its compact dimensions, cost efficiency, seamless regulation, and swift response. When deployed in distribution networks, the UPFC facilitates the creation of a Distribution Unified Power Flow Controller (DUPFC) system. The DUPFC system enhances medium voltage distribution network regulation but also affects power quality, fault characteristics, and relay protection accuracy. To address these issues, a power flow equivalent circuit model for the medium voltage distribution loop network was developed. The operating principle and steady-state model of the UPFC were investigated, based on distribution loop network parameters and power flow distribution characteristics. A UPFC control strategy was designed to create a suitable DUPFC system for the medium voltage distribution loop network, ensuring coordination between UPFC protection and the distribution system’s protection mechanisms. This system accomplishes rapid fault isolation and automatic load transfer. Finally, a simulation model based on a typical 20 kV distribution loop network structure was selected to validate the effectiveness of the UPFC control strategy and the DUPFC protection system in MATLAB/Simulink.

A Data–Physics-Driven Modeling Approach of Key Equipment for Large-Scale Distribution Network Simulation

Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.

Analysis of an improved three-phase voltage source converter with high-performance operation under unbalanced conditions

The power system is rapidly transforming into a new large-scale distributed power generation model using renewable energy. Grid-connected converters, particularly voltage control compensators like STATCOM, will be crucial to the functioning of this new situation. Voltage source converter (VSC) is one of the most commonly used topologies in grid connection converters. As a distributed power-generating device, VSCs can be utilized as a means of connecting sustainable energy sources to the power grid. The three-phase voltage source currents or voltage ripples may appear in the DC chain. This study examines the enhanced three-phase VSC, pinpoints the factors that contribute to the great performance of VSCs, and looks at future trends in three-phase VSCs. VSC is a power electronic device capable of converting DC voltages to three-phase AC voltages and is commonly used in areas such as grid connection, reactive power compensation and harmonic suppression. In practical applications, various types of grid or load disturbances pose hidden dangers to the normal operation of the VSC. Due to the presence of unbalanced grids and loads, significant double frequency.

Independence enhancement of distributed generation systems by integrating shared energy storage system and energy community with internal market

The connection of large-scale distributed generation systems, primarily distributed solar and wind power, to the public grid, will cause a considerable burden on its dispatching. How to improve the independence of distributed generation systems is crucial. This study thoroughly investigates the possibility of enhancing the independence of distributed generation systems by combining feasible solutions such as integrating energy community, installing shared energy storage, and adopting rational dispatching strategies while ensuring the benefits of multiple parties. A two-level framework for optimizing energy community scheduling and shared energy storage system sizing is proposed. The upper layer uses a multi-objective approach to optimize the size of the shared energy storage system, which ensures the economy of the shared energy storage system and the independence of the energy community. The lower layer dispatches power intending to maximize social welfare and allocates cooperative benefits through the Sharply value method, thus ensuring the interests of community participants. And a dynamic electricity price strategy in response to the imbalance between supply and demand to guide community dispatching is proposed, which reduces the peak-to-valley range while ensuring economic performance. The case results show that compared to the distributed generation systems operating alone, integrating the energy community increased the self-sufficiency and self-consumption rates of the community by 6.01 % and 6.01 %, respectively, and installing shared energy storage system increased the self-sufficiency and self-consumption rates of the community by 13.50 % and 19.35 %, respectively.

Self-triggered coordination of distributed renewable generators for frequency restoration in islanded microgrids: A low communication and computation strategy

Microgrid provides a promising solution to consume more distributed renewable energies. To coordinate the increasingly developed distributed renewable generators in a high flexibility and high efficiency way, distributed event-triggered mechanisms have been widely investigated in the literature to reduce the communication requirement and hence improve the control performance of microgrids. However, most of the event-triggered mechanisms mandate continuous calculation of complicated triggering conditions, which may in turn impose the computation burden of the controller and increase additional energy cost. To this end, this paper presents a distributed self-triggered control strategy for the frequency restoration in islanded microgrids with the aid of a linear clock. With this self-triggered solution, each distributed generator’s controller decides its own control and communication actions based on monitoring the linear clock, which excludes continuous calculation of any triggering conditions. Thus, the communication and computation costs can be reduced simultaneously. Moreover, Zeno behavior can be naturally excluded by the above design. The results of theoretical analysis and simulations show that the proposed distributed self-triggered control scheme can effectively coordinate distributed renewable generators with very low communication and computation requirements. Therefore, this research can improve the coordination efficiency of microgrids greatly, which is very useful for guiding the efficient operation of large-scale distributed renewable generators.

Reactive Power Compensation Using Electric Vehicle and Data Center by Integrating Virtual Power Plant

This article proposes a virtual power plant (VPP) theory for reactive power support consisting of electric vehicle (EV) and data center (DC) UPS battery energy storage in the power system. As enhanced grid regulations have been developed to enable large-scale distributed generation, progressive controllers are required for reactive power control considering nonlinear and industrial type load. Data center batteries are deep cycle batteries; they discharge over a much longer time and EV batteries also have great potential to absorb/release electricity from/back to the grid when needed. This paper presents the bidirectional VPP operation with a novel virtual synchronous generator (VSG)-driven reactive power controller for reactive power support. Four case studies are performed in MATLAB/Simulink platform to evaluate the performance characteristics, which include grid import/export operations, time-varying nonlinear load conditions, nonlinear industrial load conditions, and transient disturbance conditions. The obtained results validate the reactive power support in all discussed case studies.

Anti-Islanding Method Development Based on Reactive Power Variation under Grid Support Environments

As the proportion of distributed generation (DG), including Photovoltaic (PV) generation, in the power grid system increases, there are dropouts of large-scale distributed power generation sources due to some transient conditions that negatively affect the power grid stability and power quality. Accordingly, the inverter for DG generation is in a transition period, requiring more complex control performance. Anti-islanding function requirements in particular are becoming more strict because sophisticated grid-connection requirements are demanded, such as voltage ride-through, frequency ride-through, rate of change of frequency, and other functions. Thus, highly advanced anti-islanding methods are required to detect the islanding condition quickly and accurately to stop the inverter. This paper presents the improved anti-islanding method based on reactive power variation (RPV) under grid-support environments for single-phase DG inverters. In order to verify the validity of the proposed method, PSIM simulation was conducted. The proposed method meets the requirements of IEEE Std. 1547-2018 and KS C 8564:2021 by preventing islanding within 0.007 s under the newly adopted voltage/frequency trip setting, while the conventional RPV method fails.

Resilience promotion of active distribution grids under high penetration of renewables using flexible controllers

Flexible voltage controllers (FVCs), such as voltage regulation transformers (VRTs) and shunt capacitor banks (SCBs), can play a significant role in enhancing the resilience of active distribution systemS (ADS) equipped with large-scale renewable distributed generation. In this paper, a comprehensive resilience response framework is presented, which provides preventive and emergency actions both before and after hurricane events. In this study, a preventive action identifies the on/off state of dispatchable distributed generation (DDG) units and discrete settings of FVCs for both before and after a hurricane event, whereas an emergency action includes the redispatch of DDG unit, load curtailment, and voltage regulation after a hurricane event. The core of the proposed framework is a trilevel max–min robust optimization (MMRO) model, which enhances the resilience of the ADS operation problem against multistage extreme N − k contingencies and renewable power generation uncertainty. The proposed MMRO model is formulated as a mixed-integer convex programming model by relaxing nonconvex AC power flow equations into mixed-integer second-order cone relaxation (MISOCR) equations. Finally, to test the effectiveness of the proposed trilevel MMRO model, we conduct experiments on a modified IEEE-33/69 bus distribution system. The numerical results show that the proposed trilevel MMRO model is an effective model for enhancing the resilience of ADSs.

Research on the influence of switching frequency on the stability of large-scale distributed generation system

Wind power generation is generally a large-capacity low-switching frequency power station, and photovoltaic power generation is generally a small-capacity high-switching frequency power station. Large-scale access of different types of new energy power stations increased risk of grid voltage fluctuations. Therefore, in order to analyze the variation law of the stability of different types of new energy sources connected to the weak grid, it is very important to analyze the stability of inverters with different switching frequencies, but there are few studies on this issue. In this paper, the detailed sequence impedance model of the current-controlled inverter is firstly established, and its correctness is verified by frequency sweeping. Secondly, considering the control bandwidth, ripple suppression and filtering performance, the filtering parameters of inverters with different switching frequencies are designed using a unified standard. On this basis, the stability criterion based on impedance ratio is used to analyze the stability variation law of inverters with different switching frequencies under strong and weak grid conditions. Finally, the correctness and accuracy of the theoretical analysis are verified by simulation experiments.

Super resolution distribution network measurement considering distribution network topology reconstruction

As large-scale distributed generation and electric vehicles are promoted, it enhances the randomness and uncertainty of distribution network. It challenges state estimation for distribution networks, which commonly have limited measurements. To improve distribution network state perception, it is critical to utilize limited measurement and distribution network topology reconstruction to achieve the overall distribution network situation awareness. This paper proposes a distribution network measurement super-resolution model based on graph convolution neural network (GCN). The limited measurements from distribution network and multiple topologies were used as training sets. IEEE 33-nodes distribution network was used to verify the proposed method and the testing results are compared and analyzed. The testing results demonstrate the proposed GCN model can achieve distribution network situation awareness with limited measurements. It shows that the model has a good performance while the distribution network topology changes.

State Estimation of Regional Power Systems with Source-Load Two-Terminal Uncertainties

The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid. To improve the prediction accuracy of power systems with source-load two-terminal uncertainties, an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix Q0 is proposed in this paper. In the algorithm, the Q0 is used to offset the modeling error, and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems. Verification of the proposed method is implemented on the IEEE 30 node system through simulation. The results show that, compared with the traditional methods, the improved adaptive cubature Kalman filter has higher prediction accuracy, which verifies the effectiveness and accuracy of the proposed method in state estimation of the new energy power system with source-load two-terminal uncertainties.

Operational concerns and solutions in smart electricity distribution systems

Interfacing high penetration of Renewable Energy Sources (RES) with energy storage and microgrid control systems is an essential feature of future distribution grids for optimal utilization and management of Distributed Energy Resources (DERs). This feature allows distributed system operators to follow the right path to transform their traditional grids into smart grids. With the continued expansion of DERs, the current distribution grid is moving toward a carbon-free electricity system and greener energy-transportation applications. However, there are some practical concerns as well as technical and operational challenges in an interconnected power network. Therefore, this paper reviews the most prominent issues associated with smart grid, such as large-scale distributed generation integration, energy storage, energy trading, operational planning, service reliability, and cyber resiliency, in light of recent technological advancements. Through reviewing several emerging technologies, this study shows the necessary methodologies for establishing smart energy distribution. Finally, this study highlights future research prospects for a fully functional smart grid system.

Update on Nexceris’ Solid Oxide Fuel Cell Stack Technology

Over the past several years Nexceris has advanced its solid oxide fuel cell (SOFC) stack technology through innovations in materials, design, and operation. Sustainable fuel cell operation of Nexceris’ lightweight stack at high current density (0.5 – 0.7 A/cm²) and fuel utilization (70 – 80%) yields both high gravimetric power density and electrical efficiency. Stack robustness against thermal gradients, thermal cycling, and one-off events has been achieved through a combination of design modifications, sealing advancements, and operational protocols. Meanwhile, Nexceris’ stack technology maintains the key advantages of its patented FlexCell planar cell design, internal reforming capability, and tolerance to sulfur impurities in military logistic fuels.Recent and ongoing work at Nexceris includes stack demonstrations in breadboard systems and at customer sites, scale-up of stack manufacturing capabilities, and the development of a 10-kW stack module, opening the door to large-scale distributed generation and energy storage applications. This presentation will provide an update on the status and capabilities of Nexceris’ SOFC stacks and cost-saving approaches to stack fabrication.

A Distributionally Robust Power Dispatch Model for Active Distribution Network

The uncertainty of distribution network operation is increasing with the integration of large-scale renewable distributed generation (DG) units. To reduce the conservativeness of traditional robust optimization (RO) solutions, a data-driven robust optimal approach, which incorporates the superiority of both stochastic and robust approaches, is employed to solve the dispatch model in this paper. Firstly, a deterministic optimal dispatching model is established with the minimum total operation cost of distribution network; secondly, a two-stage distributed robust dispatching model is constructed based on the historical data of renewable-generators output available. The first stage of the model aims at finding optimal values under the basic prediction scenario. In the second stage, the uncertain probability distribution confidence sets with norm-1 and norm-∞ constraints are integrated to find the optimal solution under the worst probability distribution. The model is solved by column-and-constraint generation (CCG) algorithm. Numerical simulation on the IEEE 33-bus system has been performed. Comparisons with the traditional stochastic and robust approaches demonstrate the effectiveness of the proposal.

The Siting and Sizing Problem of Distributed Generation Based on a Novel Fractional Particle Swarm Optimization Algorithm

Large-scale distributed generation grid-connection brings huge economic and environmental benefits, but also threatens the stability of the grid. To make the grid consume a higher proportion of distributed generation, it is necessary to optimize the location and capacity of the distributed generation connected to the grid. Firstly, the uncertainty analysis model of wind speed, illumination intensity, and load of grid is established. Secondly, a distributed generation location and capacity planning model with the lowest annual comprehensive cost as the objective function is constructed. Then, a novel fractional particle swarm optimization algorithm is proposed, and the performance of the algorithm on complex optimization problems is tested. Finally, the simulation results of the IEEE 33-bus system example verify the rationality of the established model and the effectiveness of the proposed algorithm.

Reactive coordinated optimal operation of distributed wind generation

Large-scale distributed wind generation (DWG) integration brings new challenges to the optimal operation of the distribution network. The reactive supports from wind turbines (WTs) and reactive power resources can improve both the operation economy and renewable energy consumption. In this paper, a multi-period reactive coordinated optimal operation model for DWG in the distribution network is established. The active-reactive power coordination characteristics of two typical types of WTs are considered and the operating strategy of reactive power resources is integrated in the model. The second-order cone programming (SOCP) is developed to transform the original nonlinear power flow model into a linear and convex model, which would significantly improve the power flow calculation efficiency for DWG penetrated distribution network. The simulation results show that the integration of reactive power resources can further promote the consumption of DWG and improve the operating profits of the distribution network.

Frequency control of droop‐based low‐voltage microgrids with cobweb network topologies

When distributed generation (DG) technologies are implemented in an islanded low-voltage microgrid (LVMG), the topological architecture directly affects the frequency synchronisability. Especially in cases of high DG penetration, the synchronisability of existing traditional topological architectures for LVMGs is very limited. However, a cobweb network topology, which combines the characteristics of several traditional topological architectures, has become a novel alternative for LVMGs. In this context, a compact criterion related to the Moore–Penrose inverse of the incidence matrix for the synchronisability of an LVMG is derived. Then, based on a linear transformation and Moore–Penrose inverse theory, a comparative analysis of the synchronisability of LVMG systems with different topological architectures is presented, the results of which indicate that the synchronisability can be significantly enhanced in a cobweb network topology and that the Braess paradox can also be effectively avoided during the corresponding topological transformation. The effectiveness of the proposed synchronisation criterion is validated based on the Iceland power network, modelled as a cobweb-based LVMG with large-scale DG integration, which exhibits excellent sychronisability.