GOALI: Neural Networks and Adaptive Critic Designs For Energy Security and Sustainability

摘要提案编号：ECCS-0802047提案标题：GOALI：用于能源安全和可持续性的神经网络和自适应批判性设计PI姓名： 哈雷，RonaldPI机构：GA技术研究公司- GA技术研究所目标：能源安全和可持续性的神经网络和自适应临界算法目标和方法目标是开发一种智能广域控制器，以监测和协调包括风电场、太阳能发电场、抽水蓄能系统和其他传统发电机的电网的广域，以便在缓慢变化的条件（例如移动云层和风速变化）期间以及在瞬时扰动期间最佳地使用所有这些资源。该方法将使用自适应评论设计开发一个最佳的广域控制器，它不需要任何数学描述的电力系统。这涉及到第一次模拟，然后验证的真实的时间数字仿真器，最后，在一个小规模的2000千瓦的电力系统在科罗拉多的演示。智力MeritLearning如何以及自适应批评设计理论的规模与细胞神经网络和ObjectNets。最佳利用风能和太阳能发电场，将提高可靠性，在电网干扰期间阻尼，并协助控制室操作员。研究结果应该提供一个更好的了解多时基系统标识符和神经控制器。更广泛的影响这个项目的结果将允许太阳能和风力发电场被识别和使用的工程师以同样的方式作为其他更传统的能源，并完全集成控制，以协助维持电网的稳定性，能源安全和可持续性。包括少数民族在内的熟练劳动力将成为未来的冠军，以寻求产生“清洁”能源和减少二氧化碳和其他温室气体的排放。

AbstractProposal Number: ECCS-0802047Proposal Title: GOALI: Neural Networks and Adaptive Critic Designs For Energy Security and SustainabilityPI Name: Harley, RonaldPI Institution: GA Tech Research Corporation - GA Institute of TechnologyGOALI: NEURAL NETWORKS AND ADAPTIVE CRITIC DESIGNS FOR ENERGY SECURITY AND SUSTAINABILITYObjectives and ApproachThe objective is to develop an intelligent wide area controller to monitor and coordinate wide areas of a power network that includes a windfarm, solarfarm, pumped storage system and other traditional generators, in order to optimally use all of these resources both during slow changing conditions such as moving cloud cover, and variations in wind speed, as well as during transient disturbances. The approach will use adaptive critic designs to develop an optimal wide area controller, which does not need any mathematical descriptions of the power system. This involves first simulation, then validation on a real time digital simulator and finally, a demonstration on a small scale 2000kW power system in Colorado.Intellectual MeritLearning how well the theory of adaptive critic designs scales up with cellular neural networks and ObjectNets. Optimum utilization of the wind and solar farms, will improve reliability, damping during disturbances in the power network, and assist control room operators. The findings should provide a better understanding of multiple-time base system identifiers and neurocontrollers.Broader ImpactThe outcome of this project will allow solar and wind farms to be recognized and used by engineers in the same way as other more traditional energy sources and to be fully integrated with controls to assist in maintaining grid stability, and energy security and sustainability. Skilled manpower including minorities will be produced to serve as future champions in the quest for generating "clean" energy and reducing CO2 and other greenhouse gases emissions.