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：能源安全和可持续发展的神经网络和自适应批评设计PI名称：Harley，RonaldPI机构：GA Tech Research Corporation - GA理工学院GOALI：能源安全和可持续发展的神经网络和自适应批评设计目标和方法目标是开发一种智能广泛的智能网络区域控制器，用于监控和协调包括风电场、太阳能发电场、抽水蓄能系统和其他传统发电机在内的电力网络的广泛区域，以便在缓慢变化的条件（例如云层移动、风速变化）以及瞬态干扰期间最佳地利用所有这些资源。该方法将使用自适应批评设计来开发最佳广域控制器，该控制器不需要电力系统的任何数学描述。这包括首先进行模拟，然后在实时数字模拟器上进行验证，最后在科罗拉多州的小型 2000kW 电力系统上进行演示。智力优点学习自适应批评设计理论如何通过细胞神经网络和 ObjectNet 进行扩展。风能和太阳能发电场的最佳利用将提高可靠性、电网扰动期间的阻尼，并协助控制室操作员。研究结果应该有助于更好地理解多时基础系统标识符和神经控制器。 更广泛的影响该项目的成果将使工程师能够像其他更传统的能源一样识别和使用太阳能和风电场，并与控制系统完全集成，以协助维持电网稳定性、能源安全和可持续性。将培养包括少数族裔在内的熟练劳动力，作为未来追求“清洁”能源和减少二氧化碳和其他温室气体排放的冠军。

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.