Hybrid Distribution Network Research Articles

A low-cost strategy for systematically removing DC short-circuit currents in AC/DC-HDN

For any practically applied AC/DC hybrid distribution network (AC/DC-HDN), the hard issue of removing DC short-circuit currents must be solved by a cost-effective scheme. However, up to now, in the most published achievements of AC/DC-HDN, the systematic scheme to address the above issue is rarely found. This paper proposes a novel strategy with a low cost for solving this problem. The proposed strategy can: (i) greatly decrease the DC short-circuit current components flowing from the AC/DC converters to the fault point, (ii) fast switch off the paths of DC short-circuit current components from DG branches to the fault point, (iii) completely block the DC short-circuit current components that feed into the fault point from the capacitors paralleled on the DC ports of load branches. Also, in this paper, a new topology of DC/DC converter with a controlled zero-current output function is proposed for fast switching off the paths of DC short-circuit current components from DG branches to the fault point. The scheme of relay protection and automatic control matching with the proposed strategy is designed. The principles of the scheme and design are explained in detail. The simulation results verified the effectiveness of the proposed strategy are given.

Research on the application of distributed smart grid protection technology scheme

Abstract Distributed smart grid is an organic carrier for achieving renewable energy substitution and promoting new energy consumption. It is an important component of the construction of new power systems. To meet the current operational needs of distributed smart grid construction, a distributed smart grid protection method based on AC/DC hybrid distribution network is proposed. The distributed smart grid protection and application method proposed in this article, has good promotion and application value.

Flexibility-Oriented AC/DC Hybrid Grid Optimization Using Distributionally Robust Chance-Constrained Method

With the increasing integration of stochastic sources and loads, ensuring the flexibility of AC/DC hybrid distribution networks has become a pressing challenge. This paper aims to enhance the operational flexibility of AC/DC hybrid distribution networks by proposing a flexibility-oriented optimization framework that addresses the growing uncertainties. Notably, a comprehensive evaluation method for operational flexibility assessment is first established. Based on this, this paper further proposes a flexibility-oriented operation optimization model using the distributionally robust chance-constrained (DRCC) method. A customized solution method utilizing second-order cone relaxation and sample average approximation (SAA) is also introduced. The results of case studies indicate that the flexibility of AC/DC hybrid distribution networks is enhanced through sharing energy storage among multiple feeders, adaptive reactive power regulation using soft open points (SOPs) and static var compensators (SVCs), and power transfer between feeders via SOPs.

Development of Edge Gateway System for Data Acquisition on Transmission Line of AC/DC Hybrid Distribution Network

Development of Edge Gateway System for Data Acquisition on Transmission Line of AC/DC Hybrid Distribution Network

Distributed photovoltaic supportability consumption method considering energy storage configuration mode and random events

In order to improve the control capability of distributed photovoltaic support, a distributed photovoltaic support consumption method based on energy storage configuration mode and random events is proposed. A networked and constrained parameter analysis model for distributed photovoltaic power supply control was constructed. Based on the direct flexible mode of optical storage, an AC/DC voltage level control model for distributed solar power supply control was constructed. In the operation mode of DC hybrid distribution network, the demand response tracking identification method was used to analyze the uncertain characteristic parameters of distributed solar power supply load, and combined with the planned energy storage capacity parameters, the distributed solar power supply load and photovoltaic output were estimated. By configuring the optimal energy storage capacity, adjusting the power distribution of the microgrid, and integrating the analysis of uncertain factors and random events in the energy storage configuration mode, the design of distributed photovoltaic support consumption has been achieved. The experimental results show that the distributed photovoltaic absorption control using this method has lower load requirements, can effectively reduce the exchange power of the interconnection line, and improve the configuration scale, system reliability, and economy of the photovoltaic energy storage system.

A Method for Power Flow Calculation in AC/DC Hybrid Distribution Networks Considering the Electric Energy Routers Based on an Alternating Iterative Approach

With the advancement of new power system construction, distribution networks are gradually transforming from being a simple energy receiver and distributor to being an integrated power network that integrates sources, networks, loads, and energy storage with interactive and flexible coupling with the upper-level power grid. However, traditional distribution networks lack active control and distribution capabilities, failing to meet the demands of network transformation and upgrading. To address this issue, this paper proposes a method for solving AC/DC power flow calculation considering an electric energy router (EER) based on an alternating iterative method. Initially, the model for the multi-port EER and three types of power flow models for the AC distribution network, DC distribution network, and EER are constructed. By leveraging the properties of the EER and the hybrid power flow calculation model, a method is proposed for calculating the power flow in the AC/DC hybrid distribution network considering the EER. Finally, by solving the power flow in a medium- and low-voltage AC/DC distribution system, the adaptability of the proposed method is compared. The results demonstrate that the AC/DC hybrid distribution network power flow calculation method established in this paper, which incorporates the EER, possesses high accuracy and adaptability, with an error margin of less than 0.05%.

Start-up and Transient Support Control of AC-DC Hybrid Distribution Networks with Distributed PV Access

Abstract For AC-DC hybrid distribution networks, a large number of interconnecting converters connected to DC micro-sources and DC distribution networks in the distribution network provide a powerful aid for restoring power supply to the loads in the lost area after an accident by using the local power supply of the system, and at the same time, the power synchronisation control strategy provides a friendly power supply mode for the power supply of the interconnecting converters to the passive network. This paper analyses the start-up control of AC-DC hybrid distribution networks with distributed photovoltaic (PV) access under the scenario of interconnecting converter multi-machine co-operation in transferring power to a load area without a superordinate power supply; and puts forward a power synchronous control of interconnecting converter multi-machine co-operation to suppress power-frequency oscillation under faults of a distribution network without a superordinate power supply.

Distributed optimal Volt/Var control in power electronics dominated AC/DC hybrid distribution network

AbstractThe integration of large‐scale distributed power sources increases the voltage fluctuation in AC/DC hybrid distribution network (AD‐HDN). Power electronics devices such as photovoltaic (PV) inverters, soft open point (SOP), and voltage source converters (VSCs) can be utilized for voltage/var control (VVC) to alleviate the risk of voltage fluctuation and violation. This paper proposes a distributed optimal VVC method in power electronics dominated AD‐HDN. Firstly, the reactive power and voltage characteristics of PV inverters, SOP, and VSCs are analysed, and an optimal VVC optimization model for AD‐HDN to minimize node voltage deviation, PV curtailment, and network loss is proposed. Then, the second‐order cone (SOC) relaxation technique is used to re‐formulate the model into a convex optimization model. A distributed optimal VVC framework based on the alternating direction method of multipliers (ADMM) is constructed. Based on the residual balance principle and relaxation technique, an accelerated ADMM method is further proposed to solve the proposed model. Finally, case studies are conducted on the IEEE 33‐node and 85‐node systems to verify the superiority and effectiveness of the proposed method.

A Non-Iterative Coordinated Scheduling Method for a AC-DC Hybrid Distribution Network Based on a Projection of the Feasible Region of Tie Line Transmission Power

AC-DC hybrid distribution grids realize power transmission through tie lines. Accurately characterizing the power exchange capacity between regional grids while ensuring safe grid operation is the basis for the coordinated scheduling of resources in interconnected distribution grids. However, most of the current AC/DC hybrid models are linear, and it is challenging to ensure the accuracy criteria of the obtained feasible regions. In this paper, a two-stage multi-segment boundary approximation method is proposed to characterize the feasible region of hybrid distribution grid tie line operation. Information such as security operation constraints are mapped to the feasible region of the boundary tie line to accurately characterize the transmission exchange capacity of the tie line. To avoid the limitations of linear models, the method uses a nonlinear model to iteratively search for boundary points of the feasible region. This ensures high accuracy in approximating the real feasible region shape and capacity limitations. A convolutional neural network (CNN) is then utilized to map the given boundary and cost information to obtain an estimated equivalent operating cost function for the contact line, overcoming the inability of previous methods to capture nonlinear cost relationships. This provides the necessary cost information in a data-driven manner for the economic dispatch of hybrid AC-DC distribution networks. Numerical tests demonstrate the effectiveness of the method in improving coordination accuracy while preserving regional grid privacy. The key innovations are nonlinear modeling of the feasible domain of the contact line and nonlinear cost fitting for high-accuracy dispatch.

A Two-Stage Protection Scheme Based on Control and Protection Coordination for AC/DC Hybrid Distribution Network

A Two-Stage Protection Scheme Based on Control and Protection Coordination for AC/DC Hybrid Distribution Network

Multi-target fault ride-through strategy for transformerless MMCs under asymmetric grounding faults in AC/DC hybrid distribution networks

In AC/DC hybrid distribution networks (HDNs), when asymmetric grounding faults occur, transformerless multiterminal modular multilevel converters (MMCs) should achieve three key targets of fault ride-through (FRT): 1) limiting the unbalanced fault currents; 2) injecting currents to support grid voltages in case of disconnection from grids; and 3) eliminating the zero-sequence circulating currents (ZSCCs) from fault networks through MMCs to nonfaulted networks. However, in medium voltage-level HDNs, the line impedances are mainly resistive-inductive, and traditional current injection methods are no longer effective. Moreover, in neutral nondirect grounding networks with multiple AC voltage levels, the voltages of nonfaulted phases rise, and it is difficult for MMCs to achieve fault current control. To solve the above issues, this manuscript proposes a multi-target FRT strategy. First, negative-sequence current controllers are used to eliminate the negative-sequence fault currents. Then, to support the positive-sequence voltages of grids, optimal and suboptimal active-reactive current references based on the line impedance ratios are proposed. To help transformerless MMCs with low modulation indices eliminate zero-sequence circulating currents, two zero-sequence voltage compensation modes and an improved zero-sequence current eliminator are proposed. Finally, the proposed fault current control is verified in MATLAB/Simulink.

Multiclass transient event classification in hybrid distribution network based on co-training of fine KNN and ensemble KNN classifier

ABSTRACT A new machine learning-based method to classify the different transient events in distributed generation (DG) system has been proposed in this article. An existing hybrid DG-based network which consists of three microgrids (MGs), i.e. thermal, wind, and solar power, is used as test network to create transient conditions for both the islanding and grid-connected circumstances. The transient case studies include the symmetrical and unsymmetrical fault at distribution line, intentional islanding, variation of power demand, switching of capacitor bank, addition of nonlinear load, motor starting condition, etc. This recommended methodology starts with generating the sampled voltage signals of three different phases of different locations, and each signal has been decomposed using discrete wavelet transform. The significant features are extracted from the computed energy values of detailed wavelet coefficient for co-training of fine K-nearest neighbor (KNN) and ensemble KNN classification in the following stage. The results and the performance indices of the trained classifiers prove that the proposed method has been detected and classified all the transient events with 98% accuracy. Such type of multiple transient event classification in MG by a single algorithm is truly beneficial with respect to the power quality issues of modern power system.

A Modular Multilevel Converter Station With Multiple MVac Ports

Medium voltage (MV) ac/dc hybrid distribution network attracts much interest due to its high reliability, high power quality, and high compatibility with distributed generation and dc loads. As the key enablers to interconnect ac and dc grids, the converter stations usually adopt the modular multilevel converter (MMC) topology due to its superior modularity and scalability. Unlike the conventional stations that are implemented with multiple MMCs to accommodate multiple ac feeders, a novel multi-ac-port MMC station (MACP-MMC), which evolves from the MMC topology, is proposed in this paper to interconnect different ac feeders and facilitate flexible power exchange in the MV hybrid distribution network. In addition to the benefits inherited from the MMC, the proposed MACP-MMC also features easy multiport extension, bidirectional power flow adjustment, high power density and low cost. The operation principle, energy balance mechanism, and control strategies are elaborated. Finally, its effectiveness is verified by both simulation results in a 3-MVA case and experimental results obtained from a 3-kVA scaled-down lab prototype.

A Fully Decentralized Optimal Dispatch Scheme for an AC–DC Hybrid Distribution Network Formed by Flexible Interconnected Distribution Station Areas

A Fully Decentralized Optimal Dispatch Scheme for an AC–DC Hybrid Distribution Network Formed by Flexible Interconnected Distribution Station Areas

Optimal Scheduling of AC–DC Hybrid Distribution Network Considering the Control Mode of a Converter Station

Due to the difference in types of loads between regions and the increasing integration of random elements such as electric vehicles (EVs) and distributed generations (DGs), distribution station areas (DSAs) are facing challenges such as unbalanced load rates and voltage violations. An AC–DC hybrid distribution network formed by interconnecting AC-DSAs using flexible DC technology can not only address these issues, but also offer more efficient interfaces for EV charging piles and DC devices on the DC side. To fully leverage the advantages of the technology and coordinate dispatchable elements within each DSA, this paper proposes an optimal scheduling model, which balances the load rate between DSAs, improves voltage profiles, and considers the control mode of the converter station as a dispatchable element, taking into account its impact on the voltage deviation on the DC side. Simulation results demonstrate the effectiveness of the proposed model in balancing load rate and improving voltage profiles. Moreover, rational decision-making regarding the selection of the control mode for converter stations can effectively mitigate the voltage deviation on the DC side without deteriorating the voltage deviation on the AC side.

A Study on Energy Management and Cooperative Control Considering LVRT in a Hybrid Microgrid

Recently, the establishment of technical standards for grid connection has gained interest in academia and industry. These standards have focused on the reactive power control function of the grid-connected inverter and maintenance of grid operation, and include detailed information about the grid support function. However, remote control communication and control devices for grid support functions, and other distributed sources, such as wind power and energy storage systems, other than inverters have not been addressed. In this paper, the control of the interlinking converter (ILC) in a hybrid microgrid considering low voltage ride-through (LVRT) among grid support functions is investigated. The proposed method consists of an energy management system considering LVRT and a cooperative control scheme. In the energy management system, an algorithm capable of mode selection was constructed by applying the LVRT curve. Then, considering the LVRT situation, the allowable reactive power range of the ILC was mathematically analyzed through the cooperative control of the energy storage device and the ILC. The proposed method enables us to perform active and reactive power control of the ILC in a hybrid distribution network, considering the power factor under various conditions. This functionality, such as supplying reactive power, significantly contributes to the enhanced grid resilience with distributed power sources, including renewable energy. The proposed strategies were verified through experiments after configuring an experimental set of distributed power sources.

Dynamic reconfiguration of AC/DC hybrid distribution network considering non-ideal linear BES model

The charging and discharging process of battery energy storage (BES) directly affects its cycle aging. Therefore, considering the cycle aging cost and demand response of BES, this paper proposes a dynamic reconfiguration method of AC/DC hybrid distribution network. By sampling the operation area of charging and discharging power, the BES model in the non-ideal state is reconstructed into a linear model in the convex envelope set of sampling points. On this basis, the cycle aging cost models based on the cumulative throughput and discharge depth are established respectively, and the AC/DC hybrid distribution network reconfiguration model with the minimum comprehensive cost is constructed, and the mixed integer second-order cone programming method is used to solve it. The effectiveness and economy of the proposed reconfiguration method for AC/DC hybrid distribution network are verified by simulation on a modified 33-bus and 70-bus system.

Hybrid DC-AC microgrid energy management system using grey wolf optimized neural network

Grey wolf-optimized artificial neural networks used in DC–AC hybrid distribution networks, to regulate the energy consumption, is presented in this study. Energy management system that takes into consideration, the distributed generation, load demand, and battery state of charge are being considered. The artificial neural network have been trained, utilising the profile data, based on the energy storage system’s charging and discharging characteristics, under various distribution network power conditions. Moreover, the error rate was kept, well under 10%. The suggested energy management system, that employs an artificial neural network, has been trained to function in the optimal mode, utilising grey wolf optimization for each grid-connected power converter. Small-scale hybrid DC/AC microgrids have been developed and tested, in order to simulate and verify the proposed energy management system. The grey wolf optimized neural network energy management system has been proven to provide 99.48 % efficiency, which is superior when compared to other methods existing in the literatures.

A Coordinated Restoration Method of Hybrid AC/DC Distribution Network for Resilience Enhancement

In recent years, the frequent occurrence of extreme natural disasters has caused huge economic losses, which makes it extremely important to improve the resilience of distribution networks. With the increasing penetration of DC sources and loads, the urban distribution network is transitioning from AC to hybrid AC/DC configuration that can operate in a ring structure. The features of flexible interconnections and low network losses of DC lines can break the bottleneck of traditional restoration methods for AC distribution networks under extreme disasters, thereby further enhancing the resilience of distribution networks. Based on the interconnection feature of DC lines, this paper proposes a topology search strategy with DC lines as the core to realize the joint recovery of multiple power sources and multiple critical loads. With the obtained interconnection topology after topology search, a fault restoration model for maximizing the resilience index is established. To ensure the generality of the proposed model and explore the advantages of flexible DC power control, this paper transforms the objective function from the complex model into a mixed integer second-order cone programming (MISOCP) that can be solved directly. The optimal restoration strategy for resilience enhancement of AC/DC hybrid distribution networks can be obtained by solving the proposed MISOCP model. The numerical results in case study validate the effectiveness and superiority of the proposed method.

Coordinated scheduling of generalized energy storage in multi-voltage level AC/DC hybrid distribution network

With the diversification of electrical equipment and the large-scale popularization of renewable energy power generation, it has become a broad consensus to use schedulable resources to improve the load level and reduce network losses in power distribution networks. And meanwhile, the coverage of schedulable resources has been significantly extended due to the development of power market and network topology technologies. Based on this background, this paper proposes a coordinated scheduling model of generalized energy storage (GES) in multi-voltage level AC/DC hybrid distribution network, during which the energy storage systems (ESSs), electric vehicles (EVs), as well as transferable loads (TLs) are properly considered, and thereby the interaction in greater extent is realized. Finally, the effectiveness of the proposed model is verified through a 52-node test system, and two comparative scenarios are analyzed. Numerical results indicate that the scheduling scheme obtained from the proposed model can bring about evident reduction in network losses within the whole system.