Modular building energy management strategy based on a three-level hierarchical model predictive control is proposed in the paper. Building zones, central medium conditioning and microgrid subsystems ...are controlled independently by individual linear and nonlinear model predictive controllers, and further integrated together as levels of hierarchical coordination control structure based on price-consumption information exchange. The three-level coordination provides a holistic energy management strategy and enables significant demand response ancillary services for buildings as prosumers, while retaining the independence of required expertise in very different building subsystems. The approach is applied for daily operation scheduling of a full-scale building consisting of 248 offices. Models of building subsystems are obtained by identification procedures on measurement data. Compared to rule-based control, detailed realistic simulations show that the overall building operation cost for typical days in summer is reduced by 9-12% for level-by-level energy-optimal and by 15-24% for price-optimal, coordinated operation. The application of predictive control in the proposed way also improves the indoor comfort substantially.
This paper introduces a simple strategy for modular building energy management with explicit demand response based on a three-level hierarchical model predictive control that engages the entire ...building in optimal operation and financially viable flexibility provision. Financial viability of the assessed flexibility capacity is guaranteed regardless of the flexibility activation scenario, under the assumption that the entire building flexibility capacity is accepted. The strategy is verified on three pilot buildings. The selected pilot buildings have diverse configurations and are tested under different conditions to show the broad applicability of the developed approach. The analysis of the building flexibility is focused on particular characteristic days in the heating and cooling season and provides a comparison of the overall building operation costs for the following three control options applied to the building: hierarchical control with and without flexibility provision as well as conventional control. In this way, it is possible to quantify the benefits achievable exactly due to the advanced energy management system operation on the site. Flexibility sources and amounts within the building are analyzed in detail for each specific case.
•Hierarchical MPC-based BEMS for operation scheduling and flexibility provision.•Assessment of the entire building flexibility capacity.•Guaranteed financial viability of flexibility provision.•Verification with a detailed analysis on 3 diverse case-study buildings.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper focuses on the identification of thermodynamic models for temperature prediction in households. The proposed temperature dynamics model falls under the class of Linear Time-Invariant (LTI) ...models, making it suitable for model predictive control synthesis. However, the presence of significant and variable thermal disturbances in households adds complexity to the identification process. The performance of various prediction error methods, such as ARX, ARARMAX, and BJ models, along with simplified models incorporating persistent disturbance excitation, is analyzed. The findings highlight the substantial impact of unknown disturbances on temperature predictions, emphasizing the crucial need for accurate prediction of these disturbances for effective household heating and cooling planning. The identification and evaluation of model performance measures are conducted using two months of experimental data collected from five households. This study contributes to understanding of the significance of addressing unknown disturbances and variability in thermodynamic model identification for temperature prediction.
Smart buildings have a great potential in the energy regulation market. One of the levers that are used for the flexibility provision of buildings are the thermal comfort systems. This paper deals ...with a thermodynamic model identification for a comfort-regulated zone of a smart home with an installed air conditioner. The intended end-use of the model is model predictive control of comfort with electricity demand response over a collection of objects with such similar configuration. Typical commercial setups of closed-access air conditioners found in residential objects are considered, where there is no possibility of any data communication from the air conditioner and where the sensory equipment is quite limited due to an intended large-scale deployment. This drives the specific input-output model form where the air conditioner electricity consumption is the selected model input. The performance of different mathematical models for temperature prediction in the smart home in the heating season is analyzed and the results with quantitative measures are provided. The complete analysis is based on measurement data collected on a smart home experimental setup.
PieceWise Affine (PWA) models are used to approximate general nonlinear dynamics with an arbitrary precision. PWA model can be employed for a constrained optimal controller synthesis, whereas the ...complexity of the controller is in a large part determined with a complexity of the model. Among the prominent methods for a PWA system identification is the clustering-based identification, which is originally designed for identification of systems with a Multiple-Input Single-Output (MISO) structure. When applied for the Multiple-Input Multiple-Output (MIMO) system identification, previously used clustering-based approach implied independent estimation of PWA maps for each of the outputs, whereas the MIMO PWA model was constructed by merging the polyhedral partitions and parameters of each MISO model. PWA model obtained with the respective approach often contained a significant number of submodels, thus aggravating the controller design process. In this paper we propose a multivariate linear regression approach for the identification of a MIMO PWA model based on the clustering technique. The presented approach is a systematic extension and fully exploits all benefits of the clustering-based identification. The proposed approach is validated on a coupled MIMO system identification problem.
The article is focused on buildings with legacy one-pipe heating systems that have inherent problems with high losses and maintaining comfort when classical zone hysteresis and constant forward ...medium temperature control are applied to them. We show a great potential of predictive control to improve both comfort and energy efficiency in these systems by exploiting the possibilities existing in synchronized operation between rooms and the central heating station of the building. Optimal day-ahead scheduling based on predictive control is applied to assess the efficient operation mode of such a system which is then compared with classical reactive controls. The case study of primary school in Strem, Austria is considered and significant comfort improvement and savings possibilities are revealed.
Control in buildings has been a subject of research interest in the control community for some time. Various control methods have shown a potential for a significant savings in the building operation ...costs, whereas a large economic gain in the operation of a heating, ventilation and air conditioning (HVAC) system can be obtained by employing information about the building thermal model and the model of actuators, weather conditions, energy demand cost as well as the energy requests in the zones. This paper proposes a model predictive controller for a building chiller that exploits respective information to minimise the cost of cooling in the electricity market with volatile electrical energy prices, while ensuring comfort within the zones and respecting the power demand limitations. Obtained optimal control problem is nonlinear and the minimisation is performed by employing the successive linear programming algorithm within the feasibility region and the gradient algorithm for finding the initial feasible point. A case study HVAC system model is used to validate the performance of the proposed controller in the simulation scenario. Obtained controller minimises the cost of cooling while adhering to the imposed comfort constraints.
In the paper, a modular building energy management strategy based on a three-level hierarchical model predictive
control is applied to the daily operation scheduling of a full-scale building ...consisting of 248 offices. Such an approach
provides a holistic energy management strategy and enables significant demand response ancillary services for
buildings as prosumers, while retaining the independence of required expertise in very different building subsystems.
The three-level coordination encompasses building zones, central medium conditioning and a microgrid subsystem.
Compared to rule-based control, detailed realistic simulations for typical days in summer show that the indoor comfort
is substantially improved with a considerable reduction of the overall building operation cost. The analysis also
considers the margin of a battery storage system contribution to the operating costs reduction which underlines the
potential of software-based coordination.
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