Energy management considering load operations and forecast errors with application to HVAC systems

Abstract

This paper studies an energy management problem taking into account the relationship between the operating states and the energy consumption of the loads under forecast errors. The energy management problem is formulated as a nonlinear optimization problem, including the operation-to-energy functions and the probability of exceeding the energy supply in the constraints. An energy management algorithm is developed to seek the optimal operating states and pricing strategies for the consumers and the energy provider, respectively. Then, the globally asymptotic stability is proved for the energy management algorithm. Furthermore, the algorithm is applied to achieve energy management of distributed heating ventilation air conditioning systems. Simulation results demonstrate that the energy management algorithm converges to the optimal solution and the demand is approximately equal to the energy supply with margin for reliability.