Price/CO2 based optimization

1. Description of the Use Case

1.1. Name of the Use Case

IDArea /Domain(s)/Zone(s)Name of the Use Case
1/ Customer premises / Process, Field, Station, Operation, Enterprises, Market,UC10

1.2. Version Management

Version No.DateName of author(s)ChangesApproval status
V12020-09-25T00:00:00DTU,First DraftNone

1.3. Scope and Objectives of Use Case

ScopeThis use case is aimed at unlocking the energy flexibility potential of end-users using smart energy management system, i.e. price-based or CO2-based optimal control, to enabling their participation in demand-response programs.
Objective(s)1. Reduce building energy bills and CO2 emissions
2. Enable an automatic load response to price signals (price-based demand response programs)
3. Enhance the control strategy of power-to-heat technologies coupled with thermal storage to increase building flexibility
4. Develop forecasting algorithms to better exploit building flexibility
Related business case(s)Associate with UC7

1.4. Narrative of Use Case

Short description

Price/CO2-based control is an indirect control mechanism that can be used to drive end-users’ power consumption on the basis of signals representative of market or grid (e.g., TSO/DSO) requirements. Indeed, end-users linked to time-varying electricity or network tariffs and equipped with smart controllers can react to changes in the price of electricity over time by shifting their consumption from peak to low-tariff hours, thus reducing their energy costs on the one hand and the overall demand, during peak-hours, on the other.

Complete description

Demand response (DR) is a promising way to exploit end users’ flexibility for supporting grid balancing and management. Among DR programs, price-based programs (also known as implicit DR programs) are recognized as the most suited for engaging low-voltage end-users, like households, in grid operations. Indeed, utilities equipped with controllers capable to react to external signals, like time-varying electricity prices, can exploit storage capacities (e.g.e.g., water of swimming pools) to implement load-shifting strategies that, on the one hand, reduce their energy cost and, on the other end, provide a service to the grid (e.g., peak-shaving, congestion relief, etc.). The present use case is structured as follows: (1) Each day, the market operators upload the market clearing prices (spot prices) for the next 24 hours to the Cloud platform, where they will be accessible to all the authorized end-users. (2) X hours before Real-Time Operations (RTO), the Control Management Unit (CMU) acquires the electricity tariffs from a Cloud platform (Internet service), and previously to RTO the CMU acquires all the information (e.g., sensors data, weather forecasting, etc.) needed to optimize the end-user energy consumption over the considered control horizon (e.g. 24 hours).
(3) The CMU optimize the end-user’s consumption on the basis of the data gathered and implement the optimal control action.

1.5. Key Performance Indicatiors (KPI)

IDNameDescriptionReference to mentioned use case objectives
KPI_1Operational cost-saving (%)Energy cost reduction by participating in price-based demand response programs (e.g., €/day)1,

1.6. Use case conditions


1.7. Further information to the use case for classification/mapping

Relation to other use cases
Level of depth
Generic, regional or national relation
Nature of the use cases
Further keywords for classification
Demand Response, Distribution Network Operation, Aggregator, Energy Flexibility

1.8. General remarks

General remarks

2. Diagrams of Use Case

Overview of the use case SGAM - Component Layer SGAM - Function Layer SGAM - Communication Layer SGAM - Information  Layer SGAM - Buisness  Layer

3. Technical Details

3.1. Actors

Actor NameActor TypeActor DescriptionFurther information specific to this Use Case
Sensors, Smart metersSystemGather data at building level (e.g. indoor temperature and humidity, HP power consumption, water pool temperature) and broadcast them to the Control Management Unit through the IoT Gateway.
Controllable loadsSystemControllable devices within a building, which consume electricity, such as heat pumps, electric boilers, ventilation systems, dishwashers, fridges, freezers, dryers etc.
IoT gatewaySystemIoT Gateway to integrate multi-vendor devices with processing capability (embedded Raspberry-Pi).
Cloud PlatformSystemA cloud and web-based software platform which provides data-driven energy performance reporting, alarm, and notification system, compatible with all devices and systems such as smart meters, energy analyzers, automation systems and 3rd party software​, providing an intuitive user interface for building and district level stakeholders.
Customer Management Unit (CMU)SystemApplication that optimize the operation of the controllable loads on the basis of price/CO2 forecasts.
Load controllerSystemUnit deployed at building level to control IoT devices and loads (e.g. Heat Pump).

3.2. References

No.References TypeReferenceStatusImpact on Use CaseOrganistaor / OrganisationLink

4. Step by Step Analysis of Use Case

4.1. Overview of Scenarios

No.Scenario NameScenario DescriptionPrimary ActorTriggering EventPre-ConditionPost-Condition
PS1Energy cost/CO2 optimizationThe energy balancing/flexibility platform sends to every CMU/IoT gateway prices and forecasting and they perform the CO2/Cost optimization.Energy cost/CO2 optimization
AS1End users preference prioritizationThe CMU selects a non-optimal operation given the users preferences.End users preference prioritization


4.2. Steps – Scenarios

Scenario Name:
Energy cost/CO2 optimization
Step No.Event.Name of Process/ ActivityDescription of Process/ Activity.ServiceInformation Producer (Actor)Information Receiver (Actor)Information ExchangedRequirements, R-ID
111-15 minNoneSensors and Smart meters broadcast data to the IoT gateway.GET
2hourlyNoneThe Cloud Platform acquires market data (e.g. energy prices, CO2), complement it with additional information (e.g. weather forecasting, booking status of summer houses), and make them available to the CMU.GET
3hourlyNoneIoT gateway gathers data from the Cloud.GET
4hourlyNoneIoT gateway transmits data gathered to the Control Management Unit.GET
5Data (prices, weather forecasting, booking status) acquiredNoneThe Customer Management Unit defines the optimal control strategy to unlock the energy flexibility potential of the end users.CREATE
6Optimization problem solvedNoneThe Control Management Unit broadcasts the optimal control signals (i.e. setpoints) to the Load Controller.GET
7Optimal setpoints receivedNoneThe load controller reformats the setpoints, or operating status, of the controllable devices, and broadcasts the new values to the controlled loads.GET
8Optimal setpoints receivedNoneControllable devices update their operation parameters according to the new optimal setpoints.EXECUTE
Scenario Name:
End users preference prioritization
Step No.Event.Name of Process/ ActivityDescription of Process/ Activity.ServiceInformation Producer (Actor)Information Receiver (Actor)Information ExchangedRequirements, R-ID
1Customer setpoints receivedNoneThe customers reformat the setpoints of the controllable devicesGET
2Customer setpoints receivedNoneControllable devices update their operation parameters according to the new setpoints.EXECUTE

5. Information Exchanged

Information exchanged IDName of InformationDescription of Information ExchangedRequirement

6. Requirements (optional)

Category IdentifierNameDescriptionmRID
Req_IDReq_Name‘Price/CO2 based optimization’
1Sensor and Smart meter measurementsAir temperature and humidity, pool water temperature, electric consumption.Privacy
2Price/ CO2 dataMarket data: electricity prices and CO2 emission factor2
3Weather forecastWeather forecastingAvailability of data
4ConvenienceAdditional parameters that affect the optimal control problem (i.e., occupants’ comfort requirements).Availability of data
5Optimal control strategyOutputs of the optimal control problem solved to unlock the energy flexibility potential of end users.5
6Optimal setpointsSteering signals used to control/modify the operational status of the controllable devices.6
7Operation parametersParameters identifying the operational status of the controlled devices (e.g., on/off)7

7. Common Terms and Definitions

8. Custom Information (optional)

KeyValueRefers to Section