Automated Implicit Demand Response

1.1 Name of use case

1.2 Version management

1.3 Scope and objectives of use case

Optimization of a building’s energy consumption through automated Implicit Demand Response (DR). The communication between the building’s Customer Energy Manager System (CEMS) and the Building Automation System (BAS) can control the building’s energy consumption based on market spot prices.

The overall objectives of this use case are to: - O1 : Reduce energy costs by engaging consumers and building resources in automated Implicit Demand Response in an operational environment, - O2 : Implement CEMS as the main control point for the building's energy management : the CEMS will receive price signals and control the BAS in order to adjust and optimise energy consumption.

1.4 Narrative of use case

Implicit DR is triggered by making real time prices and/or dynamic pricing available to consumers who may adapt their consumption behaviour accordingly and consequently save money on their bill. In this use case, the Building Owner (BO) has a spot-price contract for electricity and will therefore benefit from being able to shift the building’s energy consumption (automatically) based on the actual spot price per hour. The CEMS in the building is able to receive electricity price signals and to control the flexible assets in the building in order to optimise consumption and to reduce the consumer’s electricity costs. In this use case, implicit DR will focus on the building’s hybrid heating system that is responsible for domestic hot water heating. The hybrid heating system is supplied by an exhaust air heat pump and district heating (DH). DH has seasonal prices with a peak load component that needs to be taken into account in the implicit DR optimisation. The building included in the use case is a residential building with self-contained flats.

The Building Owner (BO) has a spot price-based contract with the Retailer. This contract makes it attractive for the BO to adapt the building electricity consumption in order to save on energy expenses. In the first phase, the main resource for the implicit DR optimisation is the buildings heating system that consist of an exhaust air heat pump and district heating. The Building Owner is interested to obtain cost-savings from optimal operation of the hybrid heating system. This requires cross-sector optimisation across electricity (heat pump) and district heating. The Building Owner already has a BAS (and a Smart Meter) installed, as well as a CEMS installed. This system will allow for the optimisation of the building’s hybrid heating system by 1) shifting consumption in response to price signals received by the CEMS, and selecting which source (DH or heat pump) is used for generating the energy for heating at any time. The CEMS is able to control the BAS and thereby the electricity and district heating consumption in the building based on a predetermined set of parameters or boundaries related to minimum thermal temperature determined by the Facility Manager who is responsible for managing the heating system in the building. The CEMS will take these boundaries, the thermal inertia of the building (learned by the CEMS), heating system dynamics (learned by the CEMS), weather forecast, and time (impacts occupancy, ventilation schedules, etc that also need to be learned by the CEMS) into account when optimising the heating system control. The Facility Manager has chosen a CEMS to manage the heating system in the building automatically based on predetermined settings related to comfort and/or price settings. The comfort parameter is conditioned by a contract between the Building Owner and the residents guaranteeing residents a minimum thermal temperature. If necessary, the Facility Manager will be able to override the automatic settings.

1.5 Key performance indicators (KPI)

1.6 Use case conditions

1.7 Further information to the use case for classification/mapping

1.8 General remarks

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