In order to deal with the problems of complex optimisation model and computing speed in the multi‐objective operation control of the power distribution network, this paper is oriented to the basic ...model and process of the feeder partition decoupling method for the distribution network. Firstly, the necessity of developing partition decoupling for the distribution network is expounded according to the development status and control mode of the complex distribution network. Secondly, the objective models commonly used in the distribution network optimisation control are given to illustrate the importance of partition decoupling for the complex distribution network, including line loss and voltage offset. Finally, three general decoupling equivalent models are presented, namely Ward equivalent model, virtual generator equivalent model, and radial equivalent independent model, and then the partition decoupling equivalent process is proposed.
This research focusses on the model and basic process of the partition decoupling method for the complex distribution network with DG, which provides the foundation for the distributed parallel optimal power flow.
In this study, a partition optimisation method for distribution network is proposed to realise decoupling coordination, which provides a research basis for optimising power flow and operation ...regulation. Firstly, a partition model of distribution network is established, in which the electrical distance, parallel computing efficiency, and operation stability indexes are considered at the same time; Secondly, the AHC algorithm is used to realise the automatic search partition of the distribution network, and the class spacing measurement factors of point‐to‐point, cluster‐to‐cluster are considered in this method. Finally, the Distributed Sequential Quadratic Programming for Distributed Generation (DSQP‐DG) is introduced, and the parallel decoupling coordination of the distribution network is realised by alternate iteration of its inner and outer layers.
In this paper, a partition decoupling method of distribution network is proposed, which provides a research basis for the subsequent optimal power flow calculation and distributed operation control of distribution network. Two research directions are focussed, that is, the distribution network partition method based on AHC and the sub‐region decoupling coordination based on DSQP.
A synchronverter is an inverter that mimics synchronous generators, which offers a mechanism for power systems to control grid-connected renewable energy and facilitates smart grid integration. ...Similar to other grid-connected inverters, it needs a dedicated synchronization unit, e.g., a phase-locked loop (PLL), to provide the phase, frequency, and amplitude of the grid voltage as references. In this paper, a radical step is taken to improve the synchronverter as a self-synchronized synchronverter by removing the dedicated synchronization unit. It can automatically synchronize itself with the grid before connection and track the grid frequency after connection. This considerably improves the performance, reduces the complexity, and computational burden of the controller. All the functions of the original synchronverter, such as frequency and voltage regulation, real power, and reactive power control, are maintained. Both simulation and experimental results are presented to validate the control strategy. Experimental results have shown that the proposed control strategy can improve the performance of frequency tracking by more than 65%, the performance of real power control by 83%, and the performance of reactive power control by about 70%.
An improved nondominated sorting genetic algorithm-II (INSGA-II) has been proposed for optimal planning of multiple distributed generation (DG) units in this paper. First, multiobjective functions ...that take minimum line loss, minimum voltage deviation, and maximal voltage stability margin into consideration have been formed. Then, using the proposed INSGA-II algorithm to solve the multiobjective planning problem has been described in detail. The improved sorting strategy and the novel truncation strategy based on hierarchical agglomerative clustering are utilized to keep the diversity of population. In order to strengthen the global optimal searching capability, the mutation and recombination strategies in differential evolution are introduced to replace the original one. In addition, a tradeoff method based on fuzzy set theory is used to obtain the best compromise solution from the Pareto-optimal set. Finally, several experiments have been made on the IEEE 33-bus test case and multiple actual test cases with the consideration of multiple DG units. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been proved.
The access of large‐scale distributed generation (DG) easily leads to energy imbalance in distribution network. To deal with this issue, this paper proposes an energy optimal schedule method for ...distribution network considering the participation of source‐load‐storage aggregation groups (SAGs). Firstly, the system model consisting of distribution network layer and SAGs layer is established, and the schedule objectives and constraints of each layer are also given. Secondly, considering the fluctuation on the load side, a forecasting method based on Adaboost integrated convolutional neural networks and bidirectional long‐short term memory is proposed. Then, the improved sparrow search algorithm (ISSA) is proposed by using the tent map and Levy flight on the original sparrow search algorithm. At the same time, by introducing Pareto dominance relation and adaptive grid algorithm, the multi‐objective sparrow search algorithm (MOSSA) is derived. After that, a two‐layer optimization framework (ISSA–MOSSA) is proposed to solve the studied system. The simulation results verify the accuracy of the proposed load forecasting model, the superiority of ISSA as well as MOSSA, and the effectiveness of ISSA–MOSSA in solving the energy optimal schedule problem of the distribution system with the access of DG.
An integrated load forecasting model based on convolutional neural networks and bidirectional long‐short term memory neural network is proposed to get higher forecast accuracy of the load. And the improved sparrow search algorithmmulti‐objective sparrow search algorithm framework is proposed to solve the energy optimal schedule issue for distribution network considering the participation of source‐load‐storage aggregation groups.
In this study, a new pinning-based distributed cooperative control scheme is proposed for multi-agent system (MAS)-based autonomous microgrids. By pinning parts of selected agents, only a small ...fraction of the pinned agents are controlled by simple feedback controllers, while the other DGAs in the MAS synchronize through the communication coupling among the pinned agents in a distributed manner. The main contributions of this study are as follows: 1) the proposal of a fully distributed control for autonomous microgrids where each agent shares its operation information only with its neighbors, which obviates the requirement for a central controller and complex communication topology; 2) the proposal of a pinning-based control scheme, which reduces the number of controllers, for a predefined consensus can be reached if a small fraction of the pinned agents is controlled; and 3) the proposal of the pinning consensus under uncertain communication topologies that can meet the requirements of line switches and plug-and-play operation. Simulation results are demonstrated to verify the effectiveness and adaptability of the proposed scheme.
In order to further improve the accuracy of distributed photovoltaic (DPV) power prediction, this paper proposes a support vector machine (SVM) model based on hybrid competitive particle swarm ...optimization (HCPSO) with consideration of spatial correlation (SC), for realizing short‐term PV power prediction tasks. Firstly, the spatial correlation analysis is conducted on the distributed PV stations. The k‐means clustering method based on morphological similarity distance improvement and mutual information function is used to select the best reference station and the best delay, which generates strongly correlated PV sequences. Then, a hybrid algorithm of particle swarm optimization (PSO) and sine cosine algorithm (SCA) in a competitive framework (HCPSO) is proposed, aiming to fuse the fast convergence capability of PSO algorithm with the global search capability of SCA algorithm, while enabling the algorithm to effectively handle high‐dimensional optimization problems based on a competitive mechanism. Finally, the HCPSO algorithm is combined with SVM algorithm, which expands the applicable scenarios of the SVM model and effectively improves the accuracy of PV short‐term prediction.
This paper introduces a hybrid competitive particle swarm optimization (HCPSO) algorithm‐based support vector machine (SVM) model for short‐term forecasting of distributed photovoltaic (PV) power. It utilizes clustering methods for reference site selection and time delay determination, generating optimally correlated PV sequences. It employs a competitive mechanism‐based optimization algorithm for SVM parameter selection. Experimental results confirm improved short‐term PV forecasting accuracy.
This paper investigates the coordinated voltage control problem for smart distribution grid with the integration of distributed generation (DG). By actively participating in voltage control together ...with under-load tap changer and shunt capacitors, DG can operate more effectively in the distribution network. The objective of the proposed control method is to minimize the active power loss in the distribution system and to decrease the number of switching device operations while maintaining the grid voltage within the allowable range. Nondispatchable and dispatchable DG are both considered in the control method. To solve the mixed integer nonlinear programming problem, the trust region sequential quadratic programming method is integrated with the branch and bound approach to iteratively approximate the optimization with trust region guidance. Numerical tests on a standard 10-kV distribution system, a real 10-kV distribution system in the Sichuan province of China, and the IEEE 13-bus demonstrate the applicability of the proposed coordinated voltage control method.
This paper presents a novel distributed secondary control method for both voltage and frequency regulation in islanded microgrids. Firstly, the large-signal dynamic model of inverter-interfaced ...distributed generation (DG) is formulated in the form of a multi-input multi-output nonlinear system, which can be converted to a partly linear one using input-output feedback linearization. Then, the linear-distributed model predictive controller is designated in each DG to realize the secondary voltage control by incorporating the forecasted behaviors of the local and neighboring DG units. Through the receding optimization index of every update process, the implementation of optimal control action accelerates the convergence rate for voltage magnitudes to the reference value. Following, after transforming the nonlinear DG dynamics into a first-order linear system, a distributed proportional integral algorithm is introduced in the frequency restoration while maintaining the accurate active power sharing. Our approach utilizes the distributed architecture, which indicates superior reliability and flexibility compared to the centralized manner; moreover, it can accommodate diverse uncertainties in communication links, model parameters, and time delays. Simulation results are provided to verify the effectiveness of the proposed control methodology.
Abstract
Non‐effectively grounded power distribution systems (NGDS) are widely used in China and other countries. However, over a long time, single‐phase‐to‐ground faults (SGF) have been misjudged or ...omitted by the monitoring system, threatening the security of the power supply system and human safety. Based on the reason analysis for the omitted and misjudged SGFs in NGDS, the concept of NGDS fault eigenparameters to correctly reflect fault characteristics and a method of SGF detection based on fault eigenparameters are proposed. Then, the detection mechanism of phase voltage and fault current resistive elements for SGF is revealed. The variation characteristics of typical fault parameters changing with distribution system scale (parameter) and fault transition resistance, such as residual voltage and Zero‐sequence current (iA‐iO), are analysed. The eigenparameters of SGF in certain NGDS with specific scales/parameters are also proposed, which can correctly reflect the fault characteristics under different transition resistances.
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