Stochastic Energy Management in Smart Grid with Cyber-Physical Resilience Enhancement

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As the traditional electrical grid evolves towards future smart grid, distributed energy resources including distributed generation (DG) units such as photovoltaic (PV) panels and wind turbines, and distributed storage (DS) units such as batteries, flywheels, and electric vehicles (EVs) or electric buses (EBs) with vehicle-to-grid (V2G) capabilities, have attracted a great amount of attention from researchers in both academia and industry. Due to the flexible control and fast response of these devices, they can support a wide range of applications for both demand-side and grid-scale services. In addition to the constant progress in DG, DS, EV/EB technologies and power electronics, the development of reliable and intelligent energy management schemes has been in an urgent need in recent years. One of the greatest challenges in energy management is the randomness caused by the power generation and/or demand of distributed energy resources. Also, along with the integration of DS units including EVs/EBs at high penetration level, the charging and discharging behaviour can introduce great uncertainties into the smart grid, which can affect the reliability and stability of system operation. In addition, natural disasters such as ice storms, hurricanes, and earthquakes can cause damages to a large number of components in power distribution systems, while the data transmissions in smart grid may be prone to severe cyber attacks. Therefore, developing innovative stochastic energy management schemes with cyber-physical resilience is technically challenging but of paramount importance for the future smart grid. The long-term goal of the proposed research is to establish an architecture of intelligent energy system and build up an advanced information and communication system as a "glue" to interconnect all the energy systems (including not only electrical grid, but also other types of energy systems such as oil and natural gas systems), such that the energy can flow in industrial, commercial, residential, and transportation sectors in an efficient, reliable, secure, and sustainable way. The short-term objectives are to address the above-mentioned technical challenges and develop stochastic energy management schemes for smart grid with cyber-physical resilience in four thrusts including data-driven stochastic modeling for distributed energy resources and cyber-physical threats, stochastic energy management of sustainable buildings with distributed energy resources, stochastic energy management in smart distribution systems, and cyber-physical resilience enhancement of stochastic energy management in smart grid. The interdisciplinary nature of the proposed research will identify new opportunities for overall system optimization that are otherwise impossible in isolated approaches. The proposed research will generate new knowledge and train HQP for both power/energy and information/communication industries.