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

研究的主要目的是开发实时数字控制和保护方案，以提高电力系统的稳定性。它包括与电机行为，控制和保护方案的分析，设计和开发，从可再生能源发电，电力系统设备老化评估经济维护有关的问题的研究。 电力系统的特性是非线性的，并且由于网络配置、设备老化等的变化而变化。针对一种操作条件而设计的固定参数控制器不能跟踪系统参数的变化。随着时间的推移，它们无法提供最佳性能，系统性能会下降。为了正确操作，应重新调整控制器。它要求工厂离线，并且由于生产力损失而昂贵。一种解决方案是采用自适应控制算法，该算法连续监测系统的动态行为，并根据主要的系统操作条件实时调整控制器参数。自适应自校正控制器，自动调整控制器参数，以适应实际的操作条件，特别是适用于发电机组，已经开发出来。使用人工智能技术来设计自适应自校正控制器，是强大的，有效的和通用的正在研究应用到传统的和可再生的发电。这些控制算法扩展到电力电子设备，以提高互联电力系统的稳定性正在探索。 电力行业的一个大问题是老化的资产和缺乏技术来评估电力变压器的生命周期。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可用的数据池，公用事业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故障，从而为公用事业提供巨大的节省。 对环境退化的关切已开始向使用可再生能源发电迈出重大步伐。它导致了一个新的方向，包括风力发电场，分布式发电和微电网，这些技术特有的新的操作，控制和保护问题。研究的很大一部分是致力于可再生能源发电的各个方面，如风力发电的安全可靠的保护和控制，微电网的电压和频率控制以及分布式发电的孤岛保护。利用早期的经验与自适应和人工智能为基础的控制，新的计划正在研究，以改善操作和集成的发电可再生资源。

Primary thrust of the research is the development of real-time digital control and protection schemes for improved stability of electric power systems. It includes the study of problems relating to electric machine behavior, analysis, design and development of control and protection schemes, generation of electric power from renewable sources, and power system equipment aging assessment for economic maintenance. Power system characteristics are non-linear and change due to changes in network configuration, equipment aging, etc. The fixed parameter controllers, designed for one operating condition, cannot track changes in system parameters. With time they cannot provide optimal performance and system performance degrades. For proper operation, controllers should be retuned. It requires the plant be taken off-line and is expensive due to loss of productivity. A solution is to employ adaptive control algorithms that continuously monitor the dynamic behavior of the system and adjust controller parameters in real-time according to the prevailing system operating conditions. Adaptive self-tuning controllers, that adjust controller parameters automatically to suit actual operating conditions and particularly suitable for application to electric generating units, have been developed. Use of artificial intelligence techniques to design adaptive self-tuning controllers that are robust, effective and universal is being investigated for application to both conventional and renewable electric power generation. Extension of these control algorithms to power electronics devices to improve the stability of interconnected power systems is being explored. A big concern of the power industry is aging assets and lack of techniques to assess 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 utilities can use to commence effective condition based maintenance actions and prevent unexpected failures are being investigated to provide enormous savings to the utilities. Concerns over environmental degradation have started a major move towards electrical power generation using renewable energy sources. It has resulted in a new direction, including wind farms, distributed generation and micro-grids, with new operational, control and protection problems specific to these technologies. A good part of the research is devoted to various aspects of renewable energy generation, such as safe and reliable protection and control of wind based generation, voltage and frequency control of micro-grids and islanding protection of distributed generation. Making use of the earlier experience with adaptive and artificial intelligence based control, new schemes are being investigated to improve the operation and integration of generation from renewable resources.