Large Scale Control of Distributed Energy Resources in Modern Electric Power Systems

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University of New Brunswick


The pervasive deployment of Distributed Energy Resources (DERs) will enable the decarbonization of electric utilities and help in mitigating its carbon footprint. DERs can include renewable generation, and storage devices such as batteries and Thermostatically Controlled Loads (TCLs). A significant challenge is how to control or manage individual DERs such that the aggregated power meets the requirement for balancing generation and demand. In many jurisdictions, Air-conditioners (ACs) and Domestic Electric Water Heaters (DEWHs) are significant contributors to aggregated load. The current research focuses on aggregated control of TCLs that take the form of ACs. The control problem accepts external dispatch instructions (from the System Operator) and take action to shift the aggregated load up or down relative to the baseline aggregated load in a predictable and deterministic manner – subject to a requirement to maintain certain levels of TCL performance. The proposed research considers the: i) development of an estimator for baseline aggregated load using historical measurements of aggregated load, ii) development of a forecast algorithm over a time horizon that ranges over the next 24 hours for predicting the available capacity for shifting the load above the baseline load (reserve capacity up) and below the baseline load (reserve capacity down) and iii) development of a feedback algorithm for controlling individual DERs such that any feasible dispatch instruction (that respects the forecasted bounds on reserve capacity up and down) can be accurately executed. The research contributions include: i) a new and systematic methodology for the design and implementation of an aggregated controller that may be generalized for a variety of DERs including space heating and DEWHs, ii) a new algorithm for estimating aggregated baseline load, iii) a new algorithm for forecasting reserve capacity up and reserve capacity down that will inform dispatch instructions issued at the current time for execution at a future time.