Electricity generation from renewable energy reduces greenhouse gas emissions and, in the long term, the cost of electricity in power grids. However, there is currently no strong positive correlation between greenhouse gas intensity and electricity spot prices in Germany, despite increasing renewable energy penetration. Therefore, energy flexibility programs that rely on demand response may not be fully effective in reducing carbon emissions unless the energy market aligns consistently with carbon emission factors. To address this issue, we propose a model for joint signals consisting of power grid climate gas intensity and price signals that can achieve both environmental and economic benefits for building energy flexibility applications. Next, to assess the maximum possible flexibility hours from the grid side, we explore penalty signal threshold limits with daily and biweekly aggregation. Using a case study, we analyze energy flexibility with joint signals to explore their effect on greenhouse gas emissions and building operation cost. Our results suggest that joint signals can be more effective than a single type of signal in promoting energy flexibility.

Demand side management is becoming a promising solution to overcome the load imbalance caused by unpredictable electricity generation from renewable energy systems. To avoid the critical situations, engagement of buildings is important to support electrical grid for a reliable operation. This study investigates the potential energy flexibility of a university building by optimizing the operation of combined heat and power unit, chiller, thermal storage and ventilation system with rule based control and model predictive control. Set point of running water temperature, indoor temperature and CO 2 level are regulated as control variables. The building load profile is obtained by IDA-ICE. Historical day-ahead prices and dynamic CO 2 intensity data for the grid are used as penalty signals.