Gradient-Based Optimal Control of Batteries And HVAC in District Energy Systems

Residential and commercial buildings use nearly 75% of the overall electrical energy in the U.S., and the amount of renewable energy in the grid keeps increasing. Buildings can be an important contributor to ensure a stable grid operation because they can shift their loads to reduce peak demand and flatten the ramps of load increase and decrease. Simulation models that account for building loads and building dynamics, as well as their impact on the electricity distribution grid, are essential to assess different design and control options for buildings and electrical systems. This paper presents the use of such simulation models of dynamic building loads coupled to electrical models within a tool chain that allows efficient numerical solution of nonlinear optimization problems that aim at controlling the voltage stability and thermal comfort while minimizing energy use or energy cost. The optimization problems are formulated using the open-source JModelica software that convert them to a form in which they are solved using the nonlinear programming solver IPOPT. In this formulation, JModelica converts an infinite-dimensional optimization problem, defined on the solution of the differential equations of the simulation model, to a finite-dimensional nonlinear programming problem using computer algebra and collocation methods