Soft Open Point Research Articles

Disturbance Observer-Based Model Predictive Super-Twisting Control for Soft Open Point

This paper presents a disturbance observer-based model predictive of super-twisting control for Soft Open Point (SOP). First, with the consideration of the disturbances caused by parameter mismatches and unmodelled dynamics, a super-twisting sliding-mode observer (STO) is proposed to observe the disturbances, and the observed disturbances are introduced into the inner-loop as the compensation to improve the anti-disturbance of SOP system. Second, the outer-loop controller is designed by applying the super-twisting sliding-mode control (STC) approach to improve the dynamic performance and robustness. Third, to deal with large current harmonics by traditional model predictive control (MPC), a Three-Vector-based MPC (TV-MPC) is proposed to increase the number of voltage vectors in a sampling time. Finally, it is verified by simulations that the proposed method can reduce current harmonics, DC-side voltage setting time and improve the dynamic performance of SOP system effectively. In case of parameter mismatches, the proposed observer can observe the disturbances correctly to enhance the robustness of the SOP system.

Multi-terminal phase-changing soft open point SDP modeling for imbalance mitigation in active distribution networks

Active distribution networks (ADNs) are capable of mitigating phase imbalance caused by various operational conditions, including uneven growth of single-phase and intermittent distributed energy resources (DERs), incurring financial losses or costly infrastructure reinforcements. In this paper, the research gap for a flexible phase imbalance mitigating solution is addressed by proposing a multi-terminal phase-changing soft open point (PC-SOP). It is explored in detail on balancing the power flows and compared with other different types and ways of connection (including two-terminal and conventional). Then operational strategies based on different cases are presented for imbalance mitigation. Semidefinite programming (SDP) relaxation is utilized to convert the original non-convex nonlinear model into an SDP model which can be solved efficiently by commercial solvers. Two case studies demonstrations are conducted on IEEE 13-node and 123-node three-phase networks. It is found that multi-terminal PC-SOPs can minimize power losses by between 5.56 % and 28.98% and have better voltage control (all buses operate in the allowed voltage range [0.94, 1.10]) and less PV curtailment (reduced by at least 6.31 MW/24 h and 0.63 MW/24 h for the two test networks separately) when compared to conventional SOP technologies.

Smart soft open point to synergically improve the energy efficiencies of the interconnected electrical railways with the low voltage grids

This paper presents a novel smart soft open point (sSOP) that interconnects railway electrification system to the local low voltage (LV) distribution grid to provide additional flexibility and controllability for both networks. The proposed sSOP builds on the concept of soft open points, adding an energy storage system and embedding a rail and grid (R + G) energy management system to enable the energy transfer between the two networks at different average power levels. The smartness of the proposed soft open point is realised in the integration of an energy storage system to act as an energy buffer between these two networks of different dynamics. The paper demonstrates that the proposed sSOP improves the braking efficiency of trains and increase the local use of renewable energy through employing an integrated simulation platform between a railway and smart grid simulators that takes into account the trains' timetables as well as the daily variation of the grid loads and renewable energy generation. The results show that an appropriate design and control of the sSOP enables the recuperation of most of the braking energy available from the railway and that energy is enough to mainly supply the local power distribution grid, thereby effectively implementing the concept of smart grids.

An Overview of Soft Open Points in Electricity Distribution Networks

Soft open points (SOPs) are power electronic devices that are usually placed at normally open points of electricity distribution networks to provide flexible power control to the networks. This paper gives a comprehensive overview of both academic research and industrial practice on SOPs in electricity distribution networks. The topologies of SOPs as multi-functional power electronic devices are identified and compared, which include back-to-back voltage source converters, multi-terminal voltage source converters, unified power flow controllers, and direct AC-to-AC modular multilevel converters. The academic research is reviewed in three aspects, i.e., benefit quantification, control, and optimal siting and sizing of SOPs. The benefit quantification indices are categorized into feeder load balancing, voltage profile improvement, power losses reduction, three-phase balancing and DG hosting capacity enhancement. The control of SOPs is summarized as a three-level control structure, where the system-level and converter-level control are further discussed. For optimal siting and sizing of SOPs, problem formulation and solution methods are analyzed. Besides the academic research, practical industrial projects of SOPs worldwide are also summarized. Finally, opportunities of research and industrial application of SOPs are discussed.

Quantitative Analysis of System Operating Margin With the High Penetration of Distributed Generators in Distribution Networks

With the integration of distributed generators (DGs) and multiple types of loads, it is increasingly difficult to cope with the uncertainties of DGs, which brings challenges to the secure operation of distribution networks (DNs). Source and load cannot obtain the power balance locally, which may cause operational problems such as line power overload and node voltage violation. However, the methods for quantitatively analyzing the operating status of DNs have not yet formed a unified standard. For which reason, the concept of operating margin is proposed in this study, to represent the distance from the operating point to the boundary. In this study, to generally evaluate the operating status of DNs, the concept of node power margin is proposed first. Then the evaluation indexes including line power margin (LPM) and node voltage margin (NVM) are introduced. The quantitative calculation method for system operating margin (SOM) is further elaborated, which is supposed to be the evaluation indexes on system level. After that, the analysis process of evaluation methods for SOM is discussed. Finally, case studies are performed on the modified IEEE 33-node system to evaluate the operating margin of DNs and verify the enhancement brought by the energy storage system (ESS) and soft open point (SOP) through the flexible adjustment of power flow. The simulation results show that the distance between the DN and the security boundary is effectively quantified through the proposed method, the value can be easily calculated, and the change can be clearly reflected.

A multi-objective stochastic-information gap decision model for soft open points planning considering power fluctuation and growth uncertainty

Recently, soft open points (SOPs) attract much attention due to providing power flow control and voltage regulation to the distribution system (DS). However, multiple uncertainties and expensive capital cost are referred to as thorny issues in the SOPs planning. In this paper, a multi-objective stochastic-information gap decision (MS-IGD) model is presented to alleviate multiple uncertainties with the limited budget. First, a deterministic SOP planning model is built to minimize the comprehensive cost of distributed system operator (DSO). Then, a MS-IGD model is formulated considering power fluctuation and growth uncertainty in distributed generators (DGs) and loads. To solve this model effectively, it is transformed to a mixed integer linear programming (MILP) by the polyhedron linearization technology, linear programming theory and ε constraint algorithm. In case studies, based on a prospective DS from northern China, the SOPs planning scheme with corresponding accommodation range of multiple uncertainties is presented. Numerical results not only authenticate that the worst-case envelope bound should not be decided in advance because of the complicated relationship between multiple uncertainties and investments, but also demonstrate the negative correlation between the deviation of power fluctuation and growth uncertainty under the same budget.

Hybrid Open Points: An Efficient Tool for Increasing Network Capacity in Distribution Systems

This letter introduces the Hybrid Open Point (HOP), a device consisting of an electromechanical switch connected in parallel with a power converter, for the purpose of providing additional network capacity in interconnected distribution systems. The HOP switch is used for bulk power transfer at low-cost, whilst the HOP converter provides targeted power transfer when the HOP switch is open. The device can replace either a Normally Open Point (Type 1 HOP) or a Normally Closed Point (Type 2 HOP). Simple interconnection and teed interconnection configurations are studied considering fault level and radiality constraints, with realistic use-cases identified for both HOP types. The HOP is shown to provide secure network capacity more cost-effectively than the classical Soft Open Point.

Hydrogen-Electric Coupling Coordinated Control Strategy of Multi-Station Integrated System Based on the Honeycomb Topology

With the high-proportion accession of renewable energy and randomness of the load side in the new energy power system, unbalanced feeder power and heavy overload of the transformer caused by massive access of highly uncertain source loads become more and more serious. In order to solve the aforementioned problems, a honeycomb topology of the multi-station integrated system is proposed. The soft open point (SOP) is used as the key integrated equipment of the internal unit of a multi-station integrated system. The honeycomb grid structure is composed of flexible nodes, and the multi-station integrated system is composed of multi-network flexible interconnection. Based on the characteristics of the regional resource endowment, hydrogen energy flow is deeply coupled in parts of honeycomb grids. In order to improve the reliability and flexibility of the multi-station integrated unit, the structure of the new multi-station integrated unit, the power balance constraints on the unit, and the switching process of SOP control mode are studied. At the same time, the hydrogen electricity coupling structure and the coordinated control strategy of hydrogen electricity conversion are proposed to solve the problem of deep application of hydrogen energy. Finally, the effectiveness of the proposed multi-station integrated system is verified by using three simulation models.

Deep Reinforcement Learning-Based Adaptive Voltage Control of Active Distribution Networks with Multi-terminal Soft Open Point

The integration of highly penetrated distributed generators (DGs) aggravates the rise of voltage violations in distribution networks. Connected by multi-terminal soft open points (M−SOPs), distribution networks gradually evolve into an interconnected flexible architecture with high controllability. Distribution networks with M−SOPs can exchange active power flexibly, and M−SOPs can provide local reactive power support to alleviate voltage violations. However, conventional model-based M−SOP optimization methods cannot regulate voltage profiles adaptively owing to the rapid fluctuations of DGs. In this paper, a data-driven voltage control method is proposed for M−SOPs using a deep deterministic policy gradient network (DDPG). First, the data-driven voltage control framework is proposed for M−SOPs based on DDPG. The M−SOP−based voltage control problem is reformatted as a Markov decision process (MDP) to construct the DDPG agent. Based on real-time measurement, the DDPG agent can adaptively regulate the M−SOP operation to address the frequent DG fluctuations. Then, a multi-dimensional and dynamic boundary action masking approach is proposed to address the complex coupling in the action space of M−SOPs. Finally, the effectiveness of the proposed method was verified using the IEEE 33-node system. The results show that the proposed method can adaptively alleviate the voltage fluctuations caused by rapid DG power variations.

Self-organized Partition of Distribution Networks with Distributed Generations and Soft Open Points

Islanding operation relying on distributed generations (DGs) is anticipated to be a promising operational measure for resilience enhancement of distribution networks. In this paper, a self-organized network partition framework for controllable DGs (CDGs) is proposed for the distribution network with DGs and soft open points (SOPs) from a game-theoretic perspective. The labeled numbers of the nodes on paths between every two adjacent CDGs are used as the optimization variables in the partition formation, which can avoid a large number of invalid partition schemes. Two objectives including the weighted recovered load and the power loss are considered, which reflect the goals of maximizing the critical load recovery and minimizing the power loss, respectively. The power loss is determined through the AC power flow calculation using Newton-Raphson method considering the operational characteristics of SOPs. The partition problem is modeled as a discrete bi-objective game, which is further transformed into a continuous game model, and the existence of the Pareto-Nash equilibrium is also proved. A decentralized method is developed to solve the proposed bi-objective game relying on the local communications and a global information discovery scheme, which is more practical after the extreme events. Numerical studies on the IEEE 69-bus distribution system and a 135-bus multi-feeder system are performed to validate the effectiveness of the proposed method. The proposed model is applied in different network topologies, and compared with the centralized optimization models. The robustness of the method to communication failures is analyzed, and the scalability of the proposed model is also validated through testing it in a larger distribution network.

Soft open points based load restoration for the urban integrated energy system under extreme weather events

With frequent occurrences of extreme natural disasters such as typhoons in urban integrated energy systems (UIES), it is of great significance to cope with different kinds of disturbances. This paper proposes a load restoration method under typhoon weather for urban distribution and natural gas networks based on soft open points (SOP). Firstly, the typhoon wind speed model is introduced and the line fault rates of distribution networks under typhoons are calculated. Secondly, the gas turbine and electric-driven compressor are considered as the coupling units of the integrated electric–gas energy system, and related models are constructed. The fault analysis method of the natural gas network is proposed considering the faults in the distribution network lead by typhoons. Thirdly, SOP installed in the distribution network with the V/f control mode is applied to restore electrical loads and provide voltage support for the loads on the fault side. After that, the loads of the gas network could also be restored because of the restoration of the coupling units. Optimal energy flow is applied to determine the output of the power and gas sources, coupling units and also the loads to be restored. Finally, the fault rate of each line under typhoon disaster is analysed and the correctness and effectiveness of the resilience improving method based on SOP are verified with test systems UIES E33-G14 and UIES E123-G48.

Multi-stage supply restoration of active distribution networks with SOP integration

Supply restoration from outages is essential for improving the reliability of active distribution networks (ADNs) after fault isolation. Soft open point (SOP) can adjust the power flow among feeders and provide voltage support for power outage areas. Considering the sequential coordination of switching operation and SOP control mode selection, a multi-stage supply restoration method with SOPs is proposed for ADNs. First, the sequential energization is formulated, in which the impact of SOP control mode on restoration sequence is analyzed. By providing voltage support, the coordination of SOPs will rapidly energize the outage area and improve the voltage profile. Then, a multi-stage restoration model with SOPs is proposed, in which reconfiguration of switches and control mode selection of SOPs are coordinated in sequence to maximize the load recovery level of ADNs. Through the switching action-time mapping, secure operation is ensured during the entire supply restoration process. Finally, the effectiveness of the proposed method is validated on a modified IEEE 33-node distribution system and practical distribution networks with four-terminal SOP. Results show that the proposed method can fully exploit the potential benefits of SOPs and effectively enhance the load recovery level of ADNs.

Planning and Service Restoration Through Microgrid Formation and Soft Open Points for Distribution Network Modernization: A Review

Due to the increasing penetration of renewable energy sources, microgrids with the self-adequacy feature becomes a promising platform in distribution systems to interconnect geographically closed distributed generation units and load. Micogrids enable faster service restoration during disturbances and natural disasters, and offer improved system reliability. In this article, an extensive literature review is conducted by focusing on several important aspects of the distribution network modernization: planning and service restoration using microgrid formation and soft open points (SOPs) to achieve the improved system performance. The SOP is an emerging power electronic device in distribution systems by connecting feeders or networked microgrids to realize voltage regulation and service restoration. The future research directions in these important areas are recommended in the article.

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

A Robust Strategy for Leveraging Soft Open Points to Mitigate Load Altering Attacks

Power system cybersecurity is emerging as a critical and urgent problem to the energy sector due to the ongoing power grid modernization initiative. Load altering attack (LAA) is an important category of cyberattacks on the modern power systems, in which the attackers may damage the grid by viciously altering the remotely controllable loads (RCL) that are not properly protected. In order to mitigate the impacts of LAAs on the distribution systems, the promising soft open point (SOP) technology is deployed in this study. A two-stage optimization framework is proposed for the optimal installation and operation of SOPs for defending the distribution systems against LAAs. A chance-constrained optimization model is developed to guarantee the confidence level of the proposed two-stage model of SOPs in mitigating the impacts of LAAs. Further, a Wasserstein metric based distributionally robust chance-constrained (DRCC) optimization method is developed to ensure the robustness of the proposed model against the ambiguity of the empirical probability distribution in practice. Case studies were performed on a 69-bus test system to validate the proposed method. The results of case studies show that the proposed framework is able to mitigate the impacts of LAAs on distribution systems with the installation of SOPs. By applying the DRCC optimization method, the proposed model manages to keep satisfactory confidence levels under the ambiguous probability distributions in the case studies.

A generalized probabilistic multi‐objective method for optimal allocation of soft open point (SOP) in distribution networks

Soft open point (SOP) as a novel power electronics-based device has been introduced to control active power flow, compensate reactive power, and regulate voltage for flexible operation of distribution networks. The increasing penetration of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV) units with uncertain outputs in distribution networks increases the importance of optimal and robust allocation of SOP against multiple uncertainties to improve the performance of these networks. In this paper, a probabilistic multi-objective framework is proposed for optimal allocation of SOP in RESs included distribution networks. A novel SOP modeling in the forward-backward load flow method without any simplification is introduced. In addition, this study investigates the impact of various correlation levels between uncertain input variables in the problem. The multi-objective particle swarm optimization (MOPSO) method is used to extract Pareto-based solutions set considering the expected value of active power losses, feeder load balancing index (LBI), and investment cost of SOP as objective functions. Also, the Latin hypercube sampling (LHS) and Cholesky decomposition methods are implemented to uncertainties modeling and handling the correlations, respectively. The results of the proposed study framework are argued on the IEEE 33-node and the IEEE 118-node distribution networks.

Supply Restoration in Active Distribution Networks Based on Soft Open Points with Embedded DC Microgrids

As disturbances due to natural disasters or man-made attacks intensify awareness regarding power systems’ resilience enhancement, the scientific community concentrates on exploring state-of-the-art technologies for emergency supply restoration strategies. Recent studies are increasingly focusing on the expanded flexibility of soft open points (SOPs) compared to conventional tie-switches to increase the restoration rate of critical loads; however, the potential of this novel technology is not limited to this aspect, with SOPs being used to improve the voltage level and increase the hosting capacity of renewable energy sources (RESs). This paper proposes a deterministic model for the optimal coordination of SOPs and distributed resources in an active distribution network (ADN) aiming at re-establishing the energy supply to critical loads after a prolonged interruption occurrence. At the same time, the support of DC microgrids with integrated RESs, embedded in SOPs, for the restoration process is explored. The efficiency of the proposed optimization model is verified based on a 24-h analysis performed on the modified IEEE 33-bus system, while considering the load and generation uncertainties as well.

Coordinated planning of distributed generation and soft open points in active distribution network based on complete information dynamic game

Currently, the lack of regulation ability in distribution systems causes severe limitations in the wide grid connection of high-penetration renewable distributed generation (DG). By improving the access of SOPs, it will considerably improve the economy, flexibility, and controllability of distribution system operation. A bi-level coordinated planning model of DG and soft open points (SOPs) in an active distribution network is proposed based on a complete information dynamic game to coordinate the interests and demands of DG investors, distribution companies, and electricity consumers, and flexibly adjust the power between feeders. The model's planning stage determines the sequential decision relationship from the perspective of improving the consumption of DG and providing economic value. It analyzes the dynamic game behavior and builds the planning model to determine the optimal installation sites and capacities of DG and SOPs for different stakeholders. At the optimization stage, the operation model of the distribution network is established to reduce the network loss and voltage deviation and balance the feeder load. A hybrid optimization method is used to solve the operation-planning model using the iterative search method and mixed-integer second-order cone programming. Furthermore, numerous simulations and comparisons are carried out on IEEE 33-node system, and the results show that the proposed method can not only meet the balance of interests of different stakeholders, improve the feasibility and economy of planning schemes, but also comprehensively improve the operation state of distribution system.

Three-Vector-Based Low Complexity Model Predictive Control for Soft Open Point

Soft open point (SOP) can improve the flexibility and reliability of power supplies; thus, they are widely used in distribution network systems. Traditional single-vector model predictive control (SV-MPC) can quickly and flexibly control the power and current at both ports of the SOP. However, SV-MPC can only select one voltage vector in a sampling time, producing large current ripples, and power fluctuations. In order to solve the above problems, this paper proposes a three-vector-based low complexity model predictive control (TV-MPC). In the proposed control method, two effective voltage vectors and one zero voltage vector are selected in a sampling time. For the two-port SOP, methods are given to judge the sectors on both sides and select the voltage vectors. Furthermore, the calculation method of the distribution time is proposed as well. Finally, the effectiveness of the proposed method is verified by steady-state and dynamic-state simulation results compared with the SV-MPC.

Voltage Unbalance Compensation in Distribution Feeders Using Soft Open Points

Soft open points (SOPs) are power electronic devices that may replace conventional normally-open points in distribution networks. They can be used for active power flow control, reactive power compensation, fault isolation, and service restoration through network reconfiguration with enhanced operation flexibility and grid resiliency. Due to unbalanced loading conditions, the voltage unbalance issue, as a common problem in distribution networks, has negative impacts on distribution network operation. In this paper, a control strategy of voltage unbalance compensation for feeders using SOPs is proposed. With the power flow control, three-phase current is regulated simultaneously to mitigate the unbalanced voltage between neighboring feeders where SOPs are installed. Feeder voltage unbalance and current unbalance among three phases are compensated with the injection of negative-sequence and zero-sequence current from SOPs. Especially in response to power outages, three-phase voltage of isolated loads is regulated to be balanced by the control of SOPs connected to the feeders under faults, even if the loads are unbalanced. A MATLAB/Simulink model of the IEEE 13-bus test feeder with an SOP across feeder ends is implemented, and experimental tests on a hardware-in-the-loop platform are implemented to validate the effectiveness of the proposed control strategy.