Applications of optimal building energy system selection and operation

Abstract

Berkeley Lab has been developing the Distributed Energy Resources Customer Adoption Model for several years. Given load curves for energy services requirements in a building microgrid (µ·grid), fuel costs and other economic inputs, and a menu of available technologies, the model finds the optimum equipment fleet and operating schedule. This capability is being applied using a Software as a Service (SaaS) model. The evolution of this approach is demonstrated by description of four past and present projects: (1) a public access web site focused on solar photovoltaic generation and battery viability for large non-residential customers; (2) a building CO2 emissions reduction operations problem for a university dining hall with potential investments considered; (3) a battery and rolling operating schedule problem for a large county jail; and (4) the direct control of the solar-assisted heating ventilation and air conditioning system of a university building by providing optimised daily schedules that are automatically implemented in the building’s energy management and control system. Together these examples show that optimisation of building μ·grid design and operation can be effectively achieved using SaaS.