通讯机构：
[Zhao, Junhua] C;Chinese Univ Hong Kong Shenzhen, Shenzhen, Guangdong, Peoples R China.
关键词：
Ensemble learning;intelligent system (IS);power system;smart grid;voltage stability
摘要：
In the smart grid paradigm, growing integration of large-scale intermittent renewable energies has introduced significant uncertainties to the operations of an electric power system. This makes real-time dynamic security assessment (DSA) a necessity to enable enhanced situational-awareness against the risk of blackouts. Conventional DSA methods are mainly based on the time-domain simulation, which are insufficiently fast and knowledge-poor. In recent years, the intelligent system (IS) strategy has been identified as a promising approach to facilitate real-time DSA. While previous works mainly concentrate on the rotor angle stability, this paper focuses on another yet increasingly important dynamic insecurity phenomenon-the short-term voltage instability, which involves fast and complex load dynamics. The problem is modeled as a classification subproblem for transient voltage collapse and a prediction subproblem for unacceptable dynamic voltage deviation. A hierarchical IS is developed to address the two subproblems sequentially. The IS is based on ensemble learning of random-weights neural networks and is implemented in an offline training, a real-time application, and an online updating pattern. The simulation results on the New England 39-bus system verify its superiority in both learning speed and accuracy over some state-of-the-art learning algorithms.
关键词：
voltage regulators;stability criteria;power system security;power system reliability;static VAr compensators;cost reduction;power system economics;Pareto optimisation;probability;evolutionary computation;power system transient stability;risk management;power system dynamic stability;optimal static compensators placement;multiobjective voltage stability enhancement;power system;dynamic reactive power support;multiobjective programming model;MOP model;investment cost minimisation;unacceptable transient voltage performance minimisation;proximity minimisation;steady-state voltage collapse;Pareto optimal solutions;multiobjective decision-making;multiple contingencies;risk-based metrics;voltage stability measures;voltage stability criteria;decomposition-based multiobjective evolutionary algorithm;New England 39-bus test system
摘要：
Static compensators (STATCOMs) are able to provide rapid and dynamic reactive power support within a power system for voltage stability enhancement. While most of previous research focuses on only an either static or dynamic (short-term) voltage stability criterion, this study proposes a multi-objective programming (MOP) model to simultaneously minimise (i) investment cost, (ii) unacceptable transient voltage performance, and (iii) proximity to steady-state voltage collapse. The model aims to find Pareto optimal solutions for flexible and multi-objective decision-making. To account for multiple contingencies and their probabilities, corresponding risk-based metrics are proposed based on respective voltage stability measures. Given the two different voltage stability criteria, a strategy based on Pareto frontier is designed to identify critical contingencies and candidate buses for STATCOM connection. Finally, to solve the MOP model, an improved decomposition-based multi-objective evolutionary algorithm is developed. The proposed model and algorithm are demonstrated on the New England 39-bus test system, and compared with state-of-the-art solution algorithms.
关键词：
Active distribution network;distributed model predictive control;energy storage system
摘要：
In this letter, a distributed model predictive control strategy for battery energy storage systems is proposed to regulate voltage in distribution network with high-renewable penetration. Control actions are calculated based on communication between interconnected neighboring subsystems and a multistep receding optimization, also considering system and battery constraints. The proposed approach is shown to be highly effective through a simulation case study, indicating high potential for applications.
