Microgrids: Legal and Regulatory Hurdles for a More Resilient Energy Infrastructure

Natural disasters and climate change have made it apparent that energy infrastructure needs to be modernized and microgrids are one type of technology that can help the electricity grid become more resilient, reliable, and efficient. Different states have begun developing microgrid pilot projects including California, New York, Connecticut, and Pennsylvania. The City of Pittsburgh, Pennsylvania is the first city to propose implementing “energy districts” of microgrids that will serve as critical infrastructure, in the first phase, and then expand to commercial and community settings. This large project involves many shareholders including public utilities, government agencies, and private entities. Utilizing microgrids on such a large scale raises issues regarding its classification, as energy generation or energy storage, and whether it should be regulated by public utilities, private entities, or municipalities. In a state like Pennsylvania where the energy market has been deregulated, there is strong concern on what the public utilities involvement will be with microgrid projects. This Note focuses on the regulatory issues that are raised with the construction and operation of microgrids at such a large scale in Pittsburgh. It addresses the difficulties that arise when implementing microgrids in a deregulated energy market state such as Pennsylvania, where little to no statutory language exists regarding microgrids. It will give an overview of proposed Pennsylvania legislation that may impact a public utilities’ control over microgrid technology and the benefits and costs when examining the extent of the public utilities’ role regarding ownership and control of microgrids in a deregulated energy market

Plug-and-play Solvability of the Power Flow Equations for Interconnected DC Microgrids with Constant Power Loads

In this paper we study the DC power flow equations of a purely resistive DC power grid which consists of interconnected DC microgrids with constant-power loads. We present a condition on the power grid which guarantees the existence of a solution to the power flow equations. In addition, we present a condition for any microgrid in island mode which guarantees that the power grid remains feasible upon interconnection. These conditions provide a method to determine if a power grid remains feasible after the interconnection with a specific microgrid with constant-power loads. Although the presented condition are more conservative than existing conditions in the literature, its novelty lies in its plug-and-play property. That is, the condition gives a restriction on the to-be-connected microgrid, but does not impose more restrictions on the rest of the power grid.Comment: 8 pages, 2 figures, submitted to IEEE Conference on Decision and Control 201

Online Energy Generation Scheduling for Microgrids with Intermittent Energy Sources and Co-Generation

Microgrids represent an emerging paradigm of future electric power systems that can utilize both distributed and centralized generations. Two recent trends in microgrids are the integration of local renewable energy sources (such as wind farms) and the use of co-generation (i.e., to supply both electricity and heat). However, these trends also bring unprecedented challenges to the design of intelligent control strategies for microgrids. Traditional generation scheduling paradigms rely on perfect prediction of future electricity supply and demand. They are no longer applicable to microgrids with unpredictable renewable energy supply and with co-generation (that needs to consider both electricity and heat demand). In this paper, we study online algorithms for the microgrid generation scheduling problem with intermittent renewable energy sources and co-generation, with the goal of maximizing the cost-savings with local generation. Based on the insights from the structure of the offline optimal solution, we propose a class of competitive online algorithms, called CHASE (Competitive Heuristic Algorithm for Scheduling Energy-generation), that track the offline optimal in an online fashion. Under typical settings, we show that CHASE achieves the best competitive ratio among all deterministic online algorithms, and the ratio is no larger than a small constant 3.Comment: 26 pages, 13 figures. It will appear in Proc. of ACM SIGMETRICS, 201