Electric Power Systems - simulation, operational behaviour, control and protection

研究建议的主要推力是实时数字控制和保护方案的发展，以提高电力系统的性能和稳定性。它包括（i）与电机行为有关的具体问题的研究，（ii）电力系统控制和保护方案的分析，设计和开发，（iii）从可再生能源发电和（iv）电力系统设备老化评估，以实现可靠和经济的维护电力系统特性是非线性的。它们也可以随着时间的变化，由于在传输网络的配置，设备老化等固定参数控制器，离线设计一个固定的操作条件，不能跟踪系统参数的变化，实时。因此，随着时间的推移，即使在正常操作期间，它们也不能提供最佳性能，并且系统性能降低。为了正常运行，需要定期重新调整此类控制器。这需要关闭工厂，而且成本很高。对此的一种解决方案是采用自适应控制算法，该自适应控制算法实时地连续监测系统的动态行为，并且根据普遍的系统操作条件实时地在线自动调整控制器参数。自适应控制器，称为自校正控制器，自动调整控制器参数，以适应实际的系统条件，并特别适合于应用于发电机组，已经成功地开发。利用人工智能技术，如模糊逻辑和神经网络，设计自适应自校正控制器，是强大的，有效的和通用的应用正在研究的常规和可再生能源，如风力发电，发电。扩展这些控制算法的FACTS设备，以提高互联电力系统的运行和稳定性也正在探索。 电力行业的一个大问题是电力系统资产老化和缺乏评估电力变压器生命周期的技术。正在研究基于智能技术的算法，以挖掘和评估新出现的智能电网技术的可用数据池，电力公司可以使用这些数据池来开始有效的基于状态的维护操作，并防止意外的单元故障。这可以为公用事业节省大量资金。对环境退化的关注已经开始了使用可再生能源的大规模和小规模发电的重大举措。这导致了一个全新的方向，包括风力发电场，小规模分布式发电和微电网，这些技术具有新的操作，控制和保护问题。研究的一个重要部分是致力于可再生能源发电的各个方面，如大型风力发电设施的安全可靠的保护和控制，小规模微电网的电压和频率控制，以及分布式发电源的孤岛保护。

The primary thrust of the research proposal is the development of real-time digital control and protection schemes for improved performance and stability of electric power systems. It includes (i) the study of specific problems relating to electric machine behavior, (ii) analysis, design and development of power system control and protection schemes, (iii) generation of electric power from renewable energy sources and (iv) power system equipment aging assessment for reliable and economic maintenance Power system characteristics are non-linear. They can also change with time due to changes in transmission network configuration, equipment aging, etc. The fixed parameter controllers, designed off-line for one fixed operating condition, cannot track the changes in system parameters in real-time. Thus over time they cannot provide optimal performance even during normal operation and the system performance degrades. For proper operation, such controllers need to be retuned at regular intervals. This requires the plant to be shut down and is expensive. A solution to this is to employ adaptive control algorithms that continuously monitor the dynamic behavior of the system in real-time and automatically adjust the controller parameters on-line in real-time according to the prevalent system operating conditions. Adaptive controllers, called self-tuning controllers, that adjust controller parameters automatically to suit actual system conditions and are particularly suitable for application to electric generating units, have been successfully developed. Use of artificial intelligence techniques, such as fuzzy logic and neural networks, to design adaptive self-tuning controllers that are robust, effective and universal is being investigated for application to both conventional and renewable, such as wind power, electric power generation. Extension of these control algorithms to FACTS devices to improve the operation and stability of interconnected power systems is also being explored. A big concern of the power industry is aging power system assets and lack of techniques in assessing the life cycle of power transformers. Algorithms based on intelligent techniques to mine and evaluate the pool of data available with the newly emerging smart grid technologies that the power utilities can use to commence effective condition based maintenance actions and also prevent unexpected unit failures are being investigated. This could provide enormous savings to the utilities. Concerns over the environmental degradation have started a major move towards both large scale and small scale electrical power generation using renewable energy sources. It has resulted in a whole new direction, including wind farms, small scale distributed generation and micro-grids with new operational, control and protection problems specific to these technologies. A significant part of the research is devoted to various aspects of renewable energy generation, such as safe and reliable protection and control of large wind based generation facilities, voltage and frequency control of small scale micro-grids, and islanding protection of distributed generation sources.