The smart active residential buildings play a vital role to realize intelligent energy systems by harnessing energy flexibility from loads and storage units. This is imperative to integrate higher proportions of variable renewable energy generation and implement economically attractive demand-side participation schemes. The purpose of this paper is to develop an energy management scheme for smart sustainable buildings and analyze its efficacy when subjected to variable generation, energy storage management, and flexible demand control. This work estimate the flexibility range that can be reached utilizing deferrable/controllable energy system units such as heat pump (HP) in combination with on-site renewable energy sources (RESs), namely photovoltaic (PV) panels and wind turbine (WT), and in-house thermal and electric energy storages, namely hot water storage tank (HWST) and electric battery as back up units. A detailed HP model in combination with the storage tank is developed that accounts for thermal comforts and requirements, and defrost mode. Data analytics is applied to generate demand and generation profiles, and a hybrid energy management and a HP control algorithm is developed in this work. This is to integrate all active components of a building within a single complex-set of energy management solution to be able to apply demand response (DR) signals, as well as to execute all necessary computation and evaluation. Different capacity scenarios of the HWST and battery are used to prioritize the maximum use of renewable energy and consumer comfort preferences. A flexibility range of 22.3% is achieved for the scenario with the largest HWST considered without a battery, while 10.1% in the worst-case scenario with the smallest HWST considered and the largest battery. The results show that the active management and scheduling scheme developed to combine and prioritize thermal, electrical and storage units in buildings is essential to be studied to demonstrate the adequacy of sustainable energy buildings.
Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building
