UC11 – Minimize heating, cooling and electrical energy consumption via Model Predictive Control
Use Case UC 11 - title
UC11 – Using heat Storage to Minimize Heat Use and Provide Electrical Flexibility
Use Case UC 11 - overview
Use Case Overview
Author / organization: A. Engelmann
Date: 05/07/2017
Version No.: 1.0
Belongs to use case group (if applicable): Building Energy Management
Use Case UC 11 - description
Short Description
The occupants of the rooms have to agree on temperature limits of the building, such that they can be used as heat storages. One possible control scheme would be Model Predictive Control (MPC). The MPC controller incorporates a state space model of the building and calculates based on the available measurements an optimal control signal. An extension would be, to incorporate weather predictions in the decision. Based on that, the controller calculates optimal control inputs for the heating system, the cooling system and the concrete core activation minimizing the consumed energy of the building. The coupling between electrical consumption and heat consumption can be optimized simultaneously by using the heating/cooling system and the electrical storage.
Use Case UC 11 - details
Use Case Details
| ID | UC11 | ||
| System configuration(s) | SC Office Buildings 445 and 449 at KIT | ||
| Name of use case | Minimize heating, cooling and electrical energy consumption via Model Predictive Control | ||
| Version No. | 1.0 | ||
| Date | 05/07/2017 | ||
| Author(s) | A. Engelmann | ||
| Changes | Second version | ||
| Approval status | Draft | ||
| Scope | To meet the goal of reducing energy consumption of buildings (and thereby CO2 emissions), advanced control schemes can be used to lower the energy consumption of buildings. Thereby the incorporation of weather forecasts, advanced building models and the active use of heat/cold storages should lower the consumption of limited resources. Another aim is to reduce the needed amount of grid expansion at campus and the volatility in the grid. We try to achieve this by a combination of load shifting and the use of an electrical storage (peak shaving). [What? System under discussion, main functions, main actors] The considered building is equipped with a weather station and partial measurements of incoming heat of a distinct heating system. Whether or not we get active control access to the heating system heating system has to be clarified. Control variables could be the temperature of a heat storage, temperatures of the concrete core activation system, control of windows and the room temperature itself within certain bounds. An electrical storage is currently in planning. | ||
| Objectives | OO1: Minimize energy consumption satisfying temperature bounds in the building O2: Minimize fluctuation in building energy consumption O3: Minimize fluctuation in electrical energy consumption by means of the electrical storage (peak shaving) | ||
| Belongs to use case group (if applicable) | Building Energy Management |
Narrative of use case
| Short description | The occupants of the rooms have to agree on temperature limits of the building, such that they can be | ||
| Complete description |
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Optimality criteria
| ID | C1 | C2 | C3 | ||
| Name | Maximize efficiency | Minimize fluctuation | Minimize electrical fluctuation | ||
| Description | Minimize the energy consumption of the building in terms of the heating/cooling system. | Minimize the fluctuation in energy consumption to relieve the distinct heating system. | Minimize the fluctuation in electrical energy consumption to relieve the campus grid. | ||
| Reference to mentioned use case objectives | O1 | O2 | O3 | ||
Use case definitions
| Assumptions |
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| Prerequisites | The required sampling period depends on the time constants of the system dynamics and the required control performance. A rough estimate of one recalculation per minute is reasonable from our point of view. In case of the electrical storage the time constants are much smaller, i.e. peak shaving can be performed in time scales up to one second. |
| Graphical representation(s) of use case |
(Reference: Hysteresis modelling and displacement control of piezoelectric actuators with the frequency‐dependent behaviour using a generalized Bouc–Wen model Wei Zhu and Xiao‐Ting Rui 2016 Precision Engineering 43 299) |
| Actor name | Occupants | Predictive controller | ||
| Actor type | Human | System | ||
| Actor description | Occupants of the temperature controlled rooms | The system controllling the temperatures of the building | ||
| Further information specific | The occupants specify the maximum/minimum temperature of the building. | There is a centralized controller which controls all temperatures and heat flows simultaneously. | ||
| Alternative / complementary to sequence diagrams. | |||
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| Event | - | ||
| Name of process/ activity | - | ||
| Description of process/ activity | - | ||
| Service | - | ||
| Information producer (actor) | - | ||
| Information receiver (actor) | - | ||
| Information exchanged (IDs) | - | ||
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| Model Validation | |||
| Objective Function / Target Metrics | O1: Minimize energy consumption satisfying temperature bounds in the building O2: Minimize fluctuation in building energy consumption O3: Minimize fluctuation in electrical energy consumption by means of the electrical storage (peak shaving) | ||
| Acceptable test result | - | ||