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

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

As the risk of extreme fault conditions to power supply reliability escalates, the importance of supply recovery within active distribution networks (ADNs) is exponentially increasing. However, the utilization of a single resource strategy is insufficient to fully exploit the supply recovery potential of the ADN’s diverse and flexible resources. Therefore, a flexible resource coordination supply recovery for ADN considering multiple demand responses is proposed. This strategy utilizes distributed generation (DG) and energy storage system (ESS) as distributed power supply units, and involves the operational flexibility of soft open points (SOPs) to couple DGs with ESSs. Meanwhile, the demand response consisting of transferable and interruptible loads is taken into account, with its load regulation capability harnessed to supply recovery. A supply recovery model is established to coordinate the flexibility of source, network, and demand sides, which is further transformed into a second-order cone programming (SOCP) model to enhance solution efficiency with accuracy preservation. Simulations conducted on a modified IEEE 33-node system validate the effectiveness of the proposed strategy in maximizing supply recovery.

Soft open points (SOPs) are power electronic devices which can replace conventional normally open points in distribution networks. SOPs enable full control of active power flow between the interconnected feeders and can inject reactive power at each node to which they are connected. SOPs integrated with energy storage (ES) have been recently proposed to realize both spatial and temporal flexibility in active distribution networks. The flexibility provided by integrated ES-SOP devices will allow network operators to run their networks closer to their limits, but only if there is appropriate management of the uncertainty arising from demand and renewable generation. The only existing model of an ES-SOP uses nonconvex nonlinear equations, neglects uncertainty, and represents converter losses in an oversimplistic manner. This paper presents a robust mixed-integer convex model for the optimal scheduling of integrated ES-SOPs to ensure a zero probability of constraint violation. Losses of the subsystems comprising the ES-SOP are modeled using a proposed binary-polynomial model, enabling efficient scheduling of the energization state of subsystems to reduce no-load losses. The ES-SOP is considered in this paper to be owned by the network operator to: 1) manage power flow constraints, 2) minimize cost of losses, and 3) maximize arbitrage profit.

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

Multi-resource spatio-temporal coordinated voltage regulation for active distribution network with multiple integrated energy stations under uncertainties

Dual-layer peer-to-peer energy trading method with multiple SOPs pricing in distribution networks

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.

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.

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.

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.

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.

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.

In order to meet the high permeability and the access of large scale distributed generation, at present and in the future, active distribution network becomes the trend of smart grid research. This paper introduces the influence of distribution network voltage distribution and stability of distributed energy access based on active distribution network; The reactive power and voltage optimization control method of active power distribution network is summarized from the aspects of optimal voltage regulation measure, voltage regulation measure of power network equipment, reactive power optimal dispatch of power system, and so on. Analysis of the current status of the research, and summarized the existing active distribution network with a distributed power pickup distribution network reactive power and voltage control of the existence of some problems and the insufficiency still some problems that must be solved in the study of reactive power and voltage optimization control of active distribution network are pointed out.

Second-order conic programming model for load restoration considering uncertainty of load increment based on information gap decision theory

A Sequential Optimization Method for Soft Open Point Integrated with Energy Storage in Active Distribution Networks