An Extended Control Strategy for Weakly Meshed Distribution Networks With Soft Open Points and Distributed Generation

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.

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.

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.

A conditional value at risk based stochastic allocation of SOP in distribution networks

This study proposes an improved method of the Artificial Bee Colony (ABC) algorithm for the distribution network in scenarios where distributed generation sources and Soft Open Points (SOPs) are connected to optimize power control. Improvement is achieved by integrating the ABC algorithm with the Grenade Explosion Method and Cauchy to accelerate the ABC algorithm's speed. The objective function is considered to reduce power losses over a day. The proposed method was tested on the IEEE-33 bus test system under various scenarios: Case 1 with 3 DGs installed, Case 2 with 3 DGs and 1 SOP simultaneously installed in the distribution network, and Case 3 having the same configuration as Case 2 but operating for 24 hours. In addition to reducing power losses, the voltage at the nodes in the distribution grid was also improved, maintained above 0.95 pu and close to 1 pu. Case 3 showed that integrating a Wind Turbine (WT), two Photovoltaic (PV) generators, and one SOP during operation resulted in the lowest energy losses, smaller than a system with only one WT and two PVs, and significantly lower than the baseline system without any DGs and SOPs. Therefore, employing SOPs in a distribution network with integrated DGs can offer significant benefits in reducing energy losses.

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.

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.

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

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

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.

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.

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.

In recent years, the frequent occurrence of natural disasters has seriously threatened the security and stability of distribution networks. Amidst these natural disasters, researchers have increasingly focused on ensuring fault recovery in distribution networks. Soft open points (SOPs) are new types of power electronic devices that can effectively recover faults in distribution networks. When a fault occurs, SOPs can quickly block and isolate fault short‐circuit current, provide power access to non‐fault areas, and optimise the power flow of distribution networks. Based on the critical role of distributed generation (DG) power supply in fault recovery, this study proposes a method that leverages the synergistic capabilities of SOPs and DG to recover faults in distribution networks. By employing a binary particle swarm optimisation algorithm, this method effectively improves load recovery, reduces the number of switching operations, and minimises network loss. The proposed method was simulated and verified using the IEEE 33‐node and 99‐node systems.

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.

Soft Open Points (SOPs) and distribution network reconfiguration (DNR) are recently promoted for distribution network optimization. In this work, a multi-stage optimization including DNR, SOPs, and distributed generations (DGs) for power loss minimization, load balancing, and improving voltage security, simultaneously. Case studies are performed on a real distribution network in Cairo called a 59-node distribution network. Results show the proposed optimization approach's effectiveness in minimizing the total power loss, the load balancing index, and the fast voltage stability index by greater than 38%, 27%, and 31%, respectively.