**Flattening the Electricity Demand Profile of O** ffi**ce Buildings for Future-Proof Smart Grids**

#### **Rick Cox 1, Shalika Walker 1,\*, Joep van der Velden 2, Phuong Nguyen 1 and Wim Zeiler 1**


Received: 11 April 2020; Accepted: 3 May 2020; Published: 8 May 2020

**Abstract:** The built environment has the potential to contribute to maintaining a reliable grid at the demand side by o ffering flexibility services to a future Smart Grid. In this study, an o ffice building is used to demonstrate forecast-driven building energy flexibility by operating a Battery Electric Storage System (BESS). The objective of this study is, therefore, to stabilize/flatten a building energy demand profile with the operation of a BESS. First, electricity demand forecasting models are developed and assessed for each individual load group of the building based on their characteristics. For each load group, the prediction models show Coe fficient of Variation of the Root Mean Square Error (CVRMSE) values below 30%, which indicates that the prediction models are suitable for use in engineering applications. An operational strategy is developed aiming at meeting the flattened electricity load shape objective. Both the simulation and experimental results show that the flattened load shape objective can be met more than 95% of the time for the evaluation period without compromising the thermal comfort of users. Accurate energy demand forecasting is shown to be pivotal for meeting load shape objectives.

**Keywords:** electricity; HVAC; demand forecasting; flexibility; o ffice building; Smart Grid
