A Robust Mixed-Integer Convex Model for Optimal Scheduling of Integrated Energy Storage—Soft Open Point Devices

With the increasing amount of distributed generation (DG) integrated into electrical distribution networks, various operational problems, such as excessive power losses, over-voltage and thermal overloading issues become gradually remarkable. Innovative approaches for power flow and voltage controls are required to ensure the power quality, as well as to accommodate large DG penetrations. Using power electronic devices is one of the approaches. In this paper, a multi-objective optimization framework was proposed to improve the operation of a distribution network with distributed generation and a soft open point (SOP). An SOP is a distribution-level power electronic device with the capability of real-time and accurate active and reactive power flow control. A novel optimization method that integrates a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and a local search technique – the Taxi-cab method, was proposed to determine the optimal set-points of the SOP, where power loss reduction, feeder load balancing and voltage profile improvement were taken as objectives. The local search technique is integrated to fine tune the non-dominated solutions obtained by the global search technique, overcoming the drawback of MOPSO in local optima trapping. Therefore, the search capability of the integrated method is enhanced compared to the conventional MOPSO algorithm. The proposed methodology was applied to a 69-bus distribution network. Results demonstrated that the integrated method effectively solves the multi-objective optimization problem, and obtains better and more diverse solutions than the conventional MOPSO method. With the DG penetration increasing from 0 to 200%, on average, an SOP reduces power losses by 58.4%, reduces the load balance index by 68.3% and reduces the voltage profile index by 62.1%, all compared to the case without an SOP. Comparisons between SOP and network reconfiguration showed the outperformance of SOP in operation optimization.

An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks

Soft open points (SOPs) are power electronic devices placed at normally open points of electricity distribution networks. With millisecond-level control, SOPs are promising in constraint management of distribution networks facing the significant uncertainties from renewable power generation and customer behaviors (such as electric vehicle travelling behaviors). This paper develops a novel feasible operation region (FOR)-based method for optimal SOP control. The FOR, denoted as the allowable range of nodal power injections of distribution networks, can be used to replace the power flow equations and network constraints in a conventional optimal power flow (OPF)-based model. Due to the one-to-one correspondence between FOR boundaries and thermal/voltage constraints, FOR-based constraint management method can adapt to various measurement conditions. Moreover, the FOR constraints can be converted into a format based on line flows and node voltages, allowing for the use of real-time measurements of these operating parameters rather than the measurements of nodal power load/generation that are normally not accessible online. The proposed method is validated on the IEEE 33-node distribution network and IEEE 123-node distribution network. The performance of the method is also compared with that of conventional OPF-based control.

Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability

As part of the smart grid concept, different strategies specialized for power flow control in distribution networks have been developed. One of the possible solutions to optimize the utilization of existing capacities and increase distributed generation penetration is the implementation of Soft Open Points. Soft Open Points are modular devices based on power electronic converters that enable closing loops in the network without negative consequences regarding fault current propagation. Introducing the concept of soft open points in the distribution network enables power flow control in a particular part of the network and voltage control in the soft open point connecting nodes. The control strategy proposed in this paper addresses the main obstacle for appropriate exploitation of soft open points, defining reference values for control variables in the case of large-scale distribution systems. Furthermore, the proposed strategy also deals with data unavailability problems, that is, soft open point control under communication interruption. The proposed control algorithm incorporates centralized optimal power flow calculations and an estimation algorithm based on a multivariate polynomial regression. The optimal power flow is used to calculate the control variables in normal operation modes. The procedure based on multivariate polynomial regression was used to estimate the reference values of the control variables when the optimal power flow results were unavailable. This feature makes the proposed algorithm applicable to communication interruptions when only limited data capture is available. The algorithm proposed in this study was implemented and tested on a test network considering different scenarios. Conclusions and simulation results make this algorithm applicable to an actual soft open point controller.

In recent years, the penetration rate of intermittent distributed generation (DG) in active distribution networks has been steadily increasing, leading to prominent issues such as voltage violations and network congestion. Coordinated operation of soft open points (SOPs) and distributed energy storage systems (DESSs) enable flexible resource management in both spatial and temporal dimensions, allowing real-time voltage regulation and flow control. This enhances the controllability, sustainability, and economic efficiency of the distribution network, ultimately improving user satisfaction. The optimization of this coordinated configuration has become a central challenge in research. Taking the different characteristics of DESSs and SOPs into account, this paper proposes a coordinated configuration method by introducing local marginal price (LMP) under the configuration scheme. The framework is modeled as a three-level problem, including planning and operation levels. Initially, typical scenarios are generated to address the uncertainty of distributed generation operation. At the upper level, the DESS configuration is optimized to minimize annual operational costs, while at the middle level, SOPs are planned based on the annual comprehensive operational cost of the distribution network. At the lower level, the objective is set as social welfare maximization to reflect user satisfaction by incorporating LMP as a planning indicator. It is then transformed and solved as a mixed-integer second-order programming model with a hybrid optimization algorithm. The model is established with the modified IEEE 33-node distribution system as a case study to validate the feasibility of the proposed configuration method. The case study results demonstrate the effectiveness of the proposed approach in optimally configuring SOPs with DESSs to reduce overall annual operating costs and enhance the economic efficiency of the system.

A Combined Central and Local Voltage Control Strategy of Soft Open Points in Active Distribution Networks

Soft open point (SOP) is a new power electronic device installed in distribution network to replace the normally open point (NOP), which can achieve normalized closed-loop operation of distribution network. This paper proposes a multi-port coordinated control strategy of SOP to achieve the power flow regulation and power quality improvement of distribution network under steady state operation. The proposed strategy can improve the power quality while balancing the active power among feeders with the SOP. Three-port back to back MMC SOP is taken as studied case. Simulation results verify the effectiveness of the strategies adopted.

The Soft Open Point (SOP) is an emerging power electronics device in distribution networks to replace normally open points (NOPs). During faulty conditions, service restoration can be effectively conducted by coordinating SOPs and distributed generation (DG) units. In this paper, a novel two-stage service restoration method is proposed for a distribution network by coordinating multiple SOPs and DGs. In Stage 1, a dynamic load-shedding scheme is applied during a fault at the upstream grid or distribution substation of a distribution network, and power supply to priority loads is kept uninterrupted as much as possible with DGs. Considering the ramp rate constraints of controllable/dispatchable DGs (CDGs) in Stage 1, their active power generation is kept at the same set points as they were before the fault. In Stage 2, CDGs are dispatched to maximize restoration in the outage area. In both stages, active and reactive power of SOPs are regulated to maximize restoration. A mixedinteger nonlinear programming (MINLP) model is developed using AC power flow to formulate the proposed restoration method. The centralized (coordinated) and decentralized (uncoordinated) optimization of SOPs and DGs are conducted and compared to validate the proposed restoration method using the modified IEEE 33-node test system.

In the future, Distribution network will face many challenges due to increased acceptance of renewable resources such as photovoltaic (PV)and wind power. Typical problems that arise from increased penetration of renewable resources include overvoltage issues, load imbalances on each feeder, and fluctuations in power output. In this paper, we consider installing Soft-Open Points (SOPs) to solve these problems. SOP is a power electronic device installed at the normally-open point (NOP) of the distribution network. Typically, SOPs are comprised of voltage source converters (VSCs), which can control the power flow between the feeders. In this paper, we discuss the method of calculating the optimal operating point of a SOP using the Particle-Swarm Optimization (PSO) algorithm using the characteristics of the SOP that can independently control the active and reactive power flows. The IEEE-33 bus test system was modified to verify the proposed method and the objective function for the bus voltage deviation and the index for the total line losses can be minimized simultaneously by using the PSO algorithm to optimize the multiple objective function Algorithm.

The development of AC/DC active distribution network promotes the improvement of distribution network power supply mode. As a new-type power electronic device, Soft Open Point(SOP) has many benefits for the grid operation. In this paper, the AC/DC active distribution grid was constructed firstly and the control strategy of the back-to-back voltage source of SOP was analyzed in detail. Secondly, a mathematical model was established to reduce the system loss and to improve the node voltage over-limit condition. Considering these problems can be taken as multi-objective and nonlinear optimize problems, this paper put forward the improved genetic algorithm to solve it. Finally, the results of the simulation indicates the effectiveness of the proposed algorithm.

Soft open points (SOPs) have the ability to regulate the power flow among their terminals in a continuous manner, which can solve the problems brought by the synergy of distribution networks and distributed generation, and improve the system reliability and power supply capability. To address the current lack of quantitative measurement on the effects of SOPs, the power supply capability evaluation method for active distribution networks (ADNs) with four-terminal SOPs considering reliability is proposed. Firstly, the topology and configuration modes of four-terminal SOPs are studied, and their control modes are investigated in normal operation and supply restoration conditions. Then, using the feeder partition method, the effects of four-terminal SOPs on the power outage duration of different load areas after a fault are studied, and the reliability evaluation process for ADNs with four-terminal SOPs is developed based on the quasi-Monte Carlo method. Later, with reliability as the main constraint, the power supply capability evaluation model for ADNs with four-terminal SOPs is established, and the solution algorithm is proposed. Finally, the effectiveness and applicability of the method proposed are verified through a case study.

With the extensive grid connection of distributed generation (DG), due to the safe and stable operation restrictions of the distribution network, the abandoning of wind and solar energy become more serious. As a new type of power distribution device, soft open point (SOP) is reliable and efficient in power control, which not only effectively solve a series of problems caused by distributed power supply access, but also greatly increase the flexibility and economy of active distribution network(ADN). This paper considers the distributed power supply characteristics and demand response (DR), and establishes the planning model of SOP in the active distribution network combining planning and operation. The network layer uses the minimum integrated cost of the power distribution company as the objective function to perform SOP location and capacity. The load layer adjusts the load with the minimum cost of participating DR users. The operation optimization layer determines the power at both ends of the SOP with the minimum cost of the distribution network in each scenario as the objective function. In order to account for the timing characteristics and uncertainties of distributed power output and load, this paper analyzes the distributed power output and load curve in typical scenarios. The time-of-use electricity price mechanism is introduced to reflect the demand side characteristics of the active distribution network. In this paper, an improved multi-objective particle swarm optimization (IMOPSO) is used to solve the above model. Finally, the IEEE-33 node power distribution system is selected as an example to simulate. Through comparative analysis, it is found that the planning model of this paper can maximize economic benefits and has higher feasibility.

The intelligent soft open point (SOP) has powerful power flow regulation capabilities in the distribution network. If applied to the distribution network, it can flexibly cope with the output uncertainty of unmanageable distributed energy sources. However, considering the investment, operation, and maintenance costs, as well as the assistance of reactive power equipment, the site selection and capacity determination of SOP have become an urgent problem to be solved. This article proposes the optimal configuration strategy of SOP in a flexible interconnected distribution network, taking into account the features of distributed generation and reactive power sources. Firstly, based on the unpredictability of DG output, this paper uses improved sensitivity analysis to determine the optimal SOP installation location. Subsequently, with the optimization objective of minimizing the annual cost of the distribution network, this paper considers the characteristics of DGs, CBs, and OLCTs and uses second-order cone programming to optimize and solve SOP capacity under constraints such as trends. Finally, in the enhanced IEEE 33-node distribution system model, the effects of different scenarios on node voltage, reactive power components, and SOP location and capacity are compared.

The conservation voltage reduction (CVR) technique is a well-established technique for peak demand reduction and energy savings in the presence of voltage-sensitive loads. However, intermittent and uncertain nature of renewable energy sources such as photovoltaic generation may produce some operational issues under real-time CVR operation, which results in major problems such as undervoltage as well as increase in power losses in an active distribution network. Advanced power-electronics-based devices such as inverter-based distributed generators (IDGs) and soft open point (SOP) devices emerge as potential solutions for the aforementioned issues by providing the volt-ampere reactive (VAR) support. However, an efficient CVR methodology is much needed for proper coordination of multiple traditional volt/VAR control devices and advanced power-electronics-based devices. Therefore, this article introduces a multistage coordinated CVR methodology incorporating IDG and SOP devices for offline (i.e., day-ahead scheduling) and online (i.e., real-time dispatch) studies. For day-ahead scheduling, stochastic CVR formulation has been developed considering intermittency and uncertainties in power loads and generations. In contrast, online simulations have been performed in two stages for near-real-time operation using an inner-day rolling control model based on model-predictive control and real-time control through modified volt/VAR droop (VVD) control by optimal VVD curve selection. To validate the proposed scheme, a real-time cosimulation platform using a real-time digital simulator and a MATLAB-GAMS interface has been built. The efficacy of the proposed method has been validated on various case studies and also tested on sudden external disturbances such as sudden cloud transient, cloud cover, and substation voltage changes. Furthermore, the robustness of the proposed method has also been checked under faulty conditions. The test results demonstrate the significance of the proposed methodology on voltage violation mitigation, energy loss, energy consumption minimization, and service restoration.