Abstract
This paper presents an optimal scheduling solution for building thermal loads that simultaneously participate in the wholesale energy and frequency regulation markets. The solution combines (1) a lower-level regulation capacity reset strategy that identifies the available regulation capacity for each hour, and (2) an upper-level zone temperature scheduling algorithm to find the optimal load trajectory with a minimum net electricity cost. In the supervisory scheduling strategy, piece-wise linear approximations of representative air-conditioning equipment behaviors, derived from an offline analysis of the capacity reset mechanism, are used to predict the cooling power and regulation capacity; and a mixed-integer convex program is formulated and solved to determine the optimal control actions. In order to evaluate the performance of the developed control solution, two baseline strategies are considered, one with a conventional night setup/back control and the other utilizing an optimization procedure for minimizing the energy cost only. Five-day simulation tests were carried out for the various control strategies. Compared to the baseline night setup/back strategy, the energy-priority controller led to a 26% lower regulation credit and consequentially caused a net cost increase of 2%; the proposed bi-market control solution was able to increase the regulation credit by 118% and reduce the net electricity cost by 14%.
Highlights
One essential task for power system operation is to maintain the real-time supply and demand balance, in order to keep the system frequency stable
The plant model relied on the pseudo-optimization routine described in Equations (5)–(10) and the control model adopted the mixed-integer formulation given in Equations (26)–(30)
The optimal zone air temperature (ZAT) setpoint is determined by the supervisory scheduler, the corresponding cooling/heating load is calculated with the envelope model, and the AC power and regulation capacity are evaluated via the plant models
Summary
One essential task for power system operation is to maintain the real-time supply and demand balance, in order to keep the system frequency stable. Regulation control can be combined with load shifting techniques, e.g., through zone temperature setpoint reset, to adapt the availability of the HVAC regulation capacity in response to grid needs This control problem is often formulated as a multi-market scheduling program in which the net cost (energy cost minus the frequency regulation credit) is minimized. Recognized the difficulties of HVAC dual-market (energy plus frequency regulation) control due to the system nonlinear behaviors, and proposed a predictive scheduling solution that incorporates a zone temperature perturbation approach to estimate the regulation reserve for each hour. HVAC performance model, explicitly accounts for actual operation characteristics, such as compressor/fan speed constraints and system part-load efficiencies All these features make the proposed solution practical to implement with performance close to optimal.
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