Minimum-cost control of HVAC systems under real time prices

Abstract

Dynarmc optimal control Strategies for HVAC equipment can be deaived to "he electrical power usage or cost of operation. By acmmhg for the thermal dynamicsof the building structure and f k i h n g s and any dedicated thermal storage systems, dynamic umshaints of equipment size and permissible indoor temperature variations, in orda to improve part-load performance or to operate equipment when the price of electricity is lower. Rescheduling equipmeat operation must accolmt for storage losses, particularly when the building mass is the storage element and stored energy leaks to the e " e n L This paper focuses on the rescheduling problem rmda a vay general rate strucbae known as real-time pricing, d e s i m to Bccurately express short-tem variations in the cost to the utility for producing and txansmitting electricity. It examines the mathematical properties of the set of linear difference equations used to model t h d dynamics which are to be asymptotically stable, positive dynamic systems. This permits a much more rapid and elegant series of calculations to establish the optimal schedule than is possible with umventional h e a r programming techniques. Also presented are results from a hypothetical case study and h actual performance of an HVAC control system with storage. appmaks permit equipment use to be reschedlll~ within

A Survey of Control Technologies in the Building Automation Industry

“…Energy storage systems are able to reduce energy costs by making sure that energy is drawn from the power grid at times when costs are lower. The appearance of real-time pricing for energy in certain parts of the world is also creating a demand for more intelligent control strategies (Daryanian and Norford, 1994). Peak load management is a related strategy that seeks to shed loads in order to avoid large spikes in demand, which can incur significant cost penalties.…”

An Optimization-Based Approach for Facility Energy Management With Uncertainties

“…The problem was discretized in time and then solved by using the sequential quadratic programming (SQP) method. Dynamic control of one HVAC unit was presented in Daryanian and Norford (1994) with hourly electricity usage as the control variable. A set of heuristics was developed to minimize electricity costs under real-time pricing based on system dynamics described by linear equations.…”