Soft Open Research Articles

Multi-Agent Deep Reinforcement Learning-Based Distributed Voltage Control of Flexible Distribution Networks with Soft Open Points

The increasing number of distributed generators (DGs) leads to the frequent occurrence of voltage violations in distribution networks. The soft open point (SOP) can adjust the transmission power between feeders, leading to the evolution of traditional distribution networks into flexible distribution networks (FDN). The problem of voltage violations can be effectively tackled with the flexible control of SOPs. However, the centralized control method for SOP may make it difficult to achieve real-time control due to the limitations of communication. In this paper, a distributed voltage control method is proposed for FDN with SOPs based on the multi-agent deep reinforcement learning (MADRL) method. Firstly, a distributed voltage control framework is proposed, in which the updating algorithm of the intelligent agent of MADRL is expounded considering experience sharing. Then, a Markov decision process for multi-area SOP coordinated voltage control is proposed, where the control areas are divided based on electrical distance. Finally, an IEEE 33-node test system and a practical system in Taiwan are used to verify the effectiveness of the proposed method. It shows that the proposed multi-area SOP coordinated control method can achieve real-time control while ensuring a better control effect.

Collaborative Optimization for Active Distribution Network with Soft Open Point and Energy Storage

Background: The increasing use of high-penetration distributed clean energy has led to voltage fluctuations in the distribution network that surpass safety limits and pose challenges to economic and low-carbon operation. Traditional voltage regulation devices are unable to meet the real-time high-precision voltage control needs when encountering frequent fluctuations due to physical limitations. The Soft Open Point (SOP) can provide continuous reactive power to achieve rapid voltage regulation. Objective: We propose a collaborative optimization approach that fully considers the regulatory capabilities of SOP and energy storage to eliminate voltage violations and reduce network losses. Methods: This study introduces an active distribution network reactive power voltage optimization approach that incorporates intelligent SOP and energy storage, combining conventional devices (such as on-load tap changers and capacitor banks) with contemporary devices (such as SOP, distributed generators, and energy storage) to establish synergy. A coordinated optimization model was developed, considering various operational constraints to minimize network losses and regulate the voltage of distribution network nodes. By using linearization and quadratic relaxation, the original non-convex mixed-integer non-linear optimization model was transformed into a Mixed-Integer Second-Order Cone Programming (MISOCP) model to meet the requirements of rapid voltage regulation. Results: A case study was conducted on the IEEE 33-node test system, showing that the proposed approach effectively reduces network losses and eliminates voltage violations. Conclusion: The feasibility and effectiveness of the proposed methodology have been validated, confirming its ability to ensure the safe and economic operation of active distribution networks.

Coordinated Planning of Soft Open Points and Energy Storage Systems to Enhance Flexibility of Distribution Networks

With the large-scale penetration of distributed generation (DG), the volatility problems of active distribution networks (ADNs) have become more prominent, which can no longer be met by traditional regulation means and need to be regulated by introducing flexible resources. Soft open points (SOP) and energy storage systems (ESS) can regulate the tidal currents on spatial and temporal scales, respectively, to improve the flexibility of ADN. To this end, in-depth consideration of DG admission is given to establish flexibility assessment indicators from the power side of ADN. The conditional deep convolution generative adversarial network (C-DCGAN) is used to generate the output scenario of DG. On this basis, the SOP and ESS two-layer planning models, which take account of the potential for improvement in the flexibility of ADN, are constructed. Among them, the upper layer is the site selection and volume determination layer, which considers the economy of the system with the optimization objective of minimizing the annual integrated cost; the lower layer is the operation optimization layer, which considers the flexibility of the system and takes the highest average daily flexibility level as the optimization objective. The planning model is solved using genetic algorithm-particle swarm optimization (GA-PSO) and second-order cone programming (SOCP). The case analysis verifies the rationality and effectiveness of the planning model.

Voltage Regulation Enhanced Hierarchical Coordinated Volt/Var and Volt/Watt Control for Active Distribution Networks With Soft Open Points

Voltage Regulation Enhanced Hierarchical Coordinated Volt/Var and Volt/Watt Control for Active Distribution Networks With Soft Open Points

An Edge Intelligence-Based Framework for Online Scheduling of Soft Open Points With Energy Storage

An Edge Intelligence-Based Framework for Online Scheduling of Soft Open Points With Energy Storage

Control of Power Converters for Soft Open Points Based on a Hybrid Approach

Control of Power Converters for Soft Open Points Based on a Hybrid Approach

ЗАСТОСУВАННЯ Soft Open Point ДЛЯ ОПТИМІЗАЦІЇ ВТРАТ ЕЛЕКТРОЕНЕРГІЇ В РОЗПОДІЛЬНИХ ЕЛЕКТРИЧНИХ МЕРЕЖАХ

The increase in consumer load and the introduction of renewable energy sources lead to the need for reconstruction or modernization of distribution electrical networks. In global practice, unified devices based on modern power electronics are increasingly being used. This equipment is expensive, but in recent years in Ukraine the cost of electricity has increased significantly, which ensures the technical and economic efficiency of installing these devices. One such device is the Soft Open Point (SOP), which is used in distribution networks to reduce electrical energy consumption by compensating reactive power and redistributing active power in adjacent feeders. The article analyzes the dependence of electricity consumption on the mode of operation of the SOP and determines the regularities of optimizing the mode of its operation according to the criterion of minimum electricity consumption. A calculation was made based on real data of F-33 and F-45 of Khmelnytskyi REM using a typical daily load schedule of household consumers, which showed a reduction of active electricity losses by 14.2%. We also offer a control strategy based on balanced real and apparent component voltages between nodes of the installed SOP. The results of the control strategy were verified according to the steady-state calculation of the network with fixed loads. Then, before analyzing the results, the reduction of annual electricity costs due to the placement of the SOP was calculated, and its useful life was calculated, which is 8 years, and when the load is tripled, the useful life decreases to 2.8 years. The obtained results substantiate the possibility of abandoning the SOP, in order to optimize electricity losses, in the distribution power networks of Ukraine.

A Novel Control Strategy for Soft Open Point to Address Terminal Voltage Violations and Load Rate Imbalance in Low-Voltage Power Distribution Station Areas.

In low-voltage power distribution station areas (DSAs), sensor devices and communication networks are often inadequate. Therefore, the control strategies mainly used for soft open points (SOPs) based on global information in medium-voltage distribution networks are difficult to be directly applied to low-voltage DSAs. This paper proposes a novel control strategy for SOP that only requires collecting the local information of SOP and the load rate of transformers. It aims to address the issues faced of voltage violations at the end of feeders and the load rate imbalance among adjacent DSAs under the current high penetration of renewable energy sources. In this paper, first, a sensor network consisting of sensor devices located at the transformers and each port of the SOP is introduced for information collection. Then, based on the sensitivity relationship between the node voltage and the injected power, considering capacity and voltage safety constraints, the adjustable range of the active power output for each port of the SOP is derived. According to this range, the operating states of the DSAs are categorized into four scenarios. For each scenario, the adjustment amount of SOP output power is determined to achieve comprehensive regulation of terminal voltage and load rate of all DSAs interconnected by SOP. Finally, the effectiveness of the proposed strategy is verified based on a simulation model of three flexible interconnected DSAs established in MATLAB/Simulink.

Soft Open Point-Based Service Restoration Coordinated With Distributed Generation in Distribution Networks

Soft Open Point-Based Service Restoration Coordinated With Distributed Generation in Distribution Networks

Transient Analysis and Overcurrent Limited Strategy for Supply Restoration-Oriented Hybrid Soft Open Point

Transient Analysis and Overcurrent Limited Strategy for Supply Restoration-Oriented Hybrid Soft Open Point

Integrated Interactive Control of Distribution Systems with Multi-Building Microgrids Based on Game Theory

In the transactional processes within a multi-building microgrid system, it is imperative to safeguard stakeholders’ interests and ensure stable, economically efficient operation. Therefore, this paper proposes an integrated interactive control of distribution systems with multi-building microgrids based on game theory. Initially, an interactive framework encompassing superior power grids, distribution network operators, and multi-building microgrids is proposed. This framework establishes a master–slave game model between distribution network operators and multi-building microgrids. Additionally, it introduces the concept of Soft Open Points between building microgrids to enhance system operational safety while also reducing economic costs for distribution network operators. Subsequently, to maintain solution accuracy and optimality, it employs linearization and cone relaxation methods to transform the original model into a mixed-integer second-order cone programming model. Furthermore, it enhances an iterative search method and the price mechanism based on supply and demand ratios. The revised price mechanism serves to boost the participation of building microgrid users in energy regulation, while the iterative search method effectively resolves the equilibrium point of interest among all game participants. Finally, a simulation analysis is conducted on an IEEE-33 test system, and the effectiveness of the proposed strategy is verified by comparing three schemes.

Practical Demonstration and Novel Optimization Control for a Smart Soft Open Point to Maximize the Synergy between the DC Metro Line and the LV Distribution Grid

Practical Demonstration and Novel Optimization Control for a Smart Soft Open Point to Maximize the Synergy between the DC Metro Line and the LV Distribution Grid

Stochastic Operation of Multi-Terminal Soft Open Points in Distribution Networks with Distributionally Robust Chance-Constrained Optimization

Stochastic Operation of Multi-Terminal Soft Open Points in Distribution Networks with Distributionally Robust Chance-Constrained Optimization

Multiplexing Power Converters for Cost-Effective and Flexible Soft Open Points

The feasible set of real powers that can be transferred by a three-terminal Soft Open Point (SOP) can be increased by selecting non-uniform power ratings for each of the three ac/dc legs of the SOP, then connecting a multi-terminal switch (multiplexer) to the ac side of each of those converters to facilitate reconfiguration. This paper generalizes this concept, considering the real and reactive power that n multiplexed ac/dc converters can transfer at an m-feeder bus. The performance of the device is studied numerically for a number of ac/dc sizing strategies through the volume of the feasible set of power transfers (the `capability chart volume', CCV) and distribution system loss reduction benefits (as an exemplar network service). Upper bounds on device performance are defined by considering the performance of a novel, idealised SOP consisting of a continuum of infinitesimal reconfigurable converters. Results demonstrate that the CCV can be more than doubled, with 99% of the relative performance improvement of the idealised converter achieved with designs consisting of as few as four converters. SOP equipment costs reductions of 24% are reported, with it concluded that reconfigurable, judiciously sized ac/dc legs can yield flexible and lower cost SOPs than conventional, hard-wired approaches.

A Model Predictive Control-Based Voltage Optimization Method for Highway Transportation Power Supply Networks With Soft Open Points

A Model Predictive Control-Based Voltage Optimization Method for Highway Transportation Power Supply Networks With Soft Open Points

Expansion Planning of Soft Open Points Based Distribution System Considering EV Traffic Flow

Expansion Planning of Soft Open Points Based Distribution System Considering EV Traffic Flow

Optimal Connection Voltage of Soft Open Point and Shore-to-Ship Power Converters for Enhanced Capacitive Reactive Power Operation

Optimal Connection Voltage of Soft Open Point and Shore-to-Ship Power Converters for Enhanced Capacitive Reactive Power Operation

Differential Detection of Feeder and Mesh Impedances Through a Series–Parallel Direct-Injection Soft Open Point

Differential Detection of Feeder and Mesh Impedances Through a Series–Parallel Direct-Injection Soft Open Point

Optimal Configuration for Soft Open Point Based on Scenario Generation of Wind Power and Photovoltaic Output

Soft Open Point (SOP) is a new type of fully controlled power electronic device. The use of SOPs can greatly improve the efficiency, flexibility, and controllability of distribution networks. However, considering that SOPs are expensive and have high maintenance costs, the installation capacity and location of SOPs need to be optimized. In this paper, we propose an SOP optimization configuration method considering the stochasticity and correlation of wind and PV power generation. First, considering the uncertainty and negative correlation of wind and PV power output, the probability density distribution function is generated using Copula theory and historical data. Then, the optimal location of the SOPs is determined by a cluster discovery algorithm and the Power Loss Sensitivity Index (PLSI). Finally, the capacity of the SOP is determined by minimizing the integrated cost of the network over a year, and the capacity of the SOP is solved by the conic curve programming method. The superiority of the proposed method is verified in this study at the IEEE-33 node test system.

Some Classes of Soft Functions Defined by Soft Open Sets Modulo Soft Sets of the First Category

Soft continuity can contribute to the development of digital images and computational topological applications other than the field of soft topology. In this work, we study a new class of generalized soft continuous functions defined on the class of soft open sets modulo soft sets of the first category, which is called soft functions with the Baire property. This class includes all soft continuous functions. More precisely, it contains various classes of weak soft continuous functions. The essential properties and operations of the soft functions with the Baire property are established. It is shown that a soft continuous with values in a soft second countable space is identical to a soft function with the Baire property, apart from a topologically negligible soft set. Then we introduce two more subclasses of soft functions with the Baire property and examine their basic properties. Furthermore, we characterize these subclasses in terms of soft continuous functions. At last, we present a diagram that shows the relationships between the classes of soft functions defined in this work and those that exist in the literature.