A Data Analytics Framework for Smart Grids: Spatio-temporal Wind Power Analysis and Synchrophasor Data Mining

Under the framework of intelligent management of power grids by leveragingadvanced information, communication and control technologies, a primary objectiveof this study is to develop novel data mining and data processing schemes for severalcritical applications that can enhance the reliability of power systems. Specifically,this study is broadly organized into the following two parts: I) spatio-temporal windpower analysis for wind generation forecast and integration, and II) data mining andinformation fusion of synchrophasor measurements toward secure power grids.Part I is centered around wind power generation forecast and integration.First, a spatio-temporal analysis approach for short-term wind farm generation fore-casting is proposed. Specifically, using extensive measurement data from an actualwind farm, the probability distribution and the level crossing rate of wind farm gen-eration are characterized using tools from graphical learning and time-series analysis.Built on these spatial and temporal characterizations, finite state Markov chain mod-els are developed, and a point forecast of wind farm generation is derived using theMarkov chains. Then, multi-timescale scheduling and dispatch with stochastic windgeneration and opportunistic demand response is investigated.Part II focuses on incorporating the emerging synchrophasor technology intothe security assessment and the post-disturbance fault diagnosis of power systems.First, a data-mining framework is developed for on-line dynamic security assessmentby using adaptive ensemble decision tree learning of real-time synchrophasor measure-ments. Under this framework, novel on-line dynamic security assessment schemes aredevised, aiming to handle various factors (including variations of operating conditions,forced system topology change, and loss of critical synchrophasor measurements) thatcan have significant impact on the performance of conventional data-mining based on-