Abstract
The built environment has the potential to contribute to maintaining a reliable grid at the demand side by offering flexibility services to a future Smart Grid. In this study, an office 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 Coefficient 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.
Highlights
The European Union agrees on drastically lowering CO2 emissions in order to mitigate the effects of climate change [1,2]
Step 1: Prediction models are established for each load group and the performance metrics that are used to analyze prediction accuracy are described; Step 2: The operational strategy of the Battery Electric Storage System (BESS) is described alongside key performance indicators (KPIs) that are used to quantify the impact of the energy flexibility provided; Step 3: The implementation procedure in the real Building Management System (BMS) system is described
HVAC control unit load group (EAHU&controls ) against the outdoor temperature (Toutdoor ), a parametric and HVAC control unit load group (EAHU&controls) against the outdoor temperature (Toutdoor), a parametric approach was considered for demand prediction
Summary
The European Union agrees on drastically lowering CO2 emissions in order to mitigate the effects of climate change [1,2]. In the Netherlands, electricity generation is mostly achieved by means of fossil fuels and is responsible for a significant portion of the total emissions [3]. A transition to more sustainable energy generation is necessary within the country to decarbonize the grid [4,5]. When transitioning towards a low-carbon society, sustainable generation, and energy saving on the demand side is even more important [6,7]. Transport and the built environment account for approximately 24% and 36% of total energy consumption in the Netherlands and are responsible for much of the emissions due to fossil fuels [3,8]. It is evident that an effective transition to a sustainable future requires technologies on the demand side [9,10]
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