scholarly journals A Methodology for the Enhancement of the Energy Flexibility and Contingency Response of a Building Through Predictive Control of Passive and Active Storage

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1387
Author(s):  
Jennifer Date ◽  
José A. Candanedo ◽  
Andreas K. Athienitis
Keyword(s):  
Predictive Control ◽  
Thermal Energy ◽  
Control Strategies ◽  
Thermal Storage ◽  
Building Energy ◽  
Load Management ◽  
Active Storage ◽  
Rate Structure ◽  
Heating Load ◽  
Zone Temperature

Optimal management of thermal energy storage in a building is essential to provide predictable energy flexibility to a smart grid. Active technologies such as Electric Thermal Storage (ETS) can assist in building heating load management and can complement the building’s passive thermal storage capacity. The presented paper outlines a methodology that utilizes the concept of Building Energy Flexibility Index (BEFI) and shows that implementing Model Predictive Control (MPC) with dedicated thermal storage can provide predictable energy flexibility to the grid during critical times. When the utility notifies the customer 12 h before a Demand Response (DR) event, a BEFI up to 65 kW (100% reduction) can be achieved. A dynamic rate structure as the objective function is shown to be successful in reducing the peak demand, while a greater reduction in energy consumption in a 24-hour period is seen with a rate structure with a demand charge. Contingency reserve participation was also studied and strategies included reducing the zone temperature setpoint by 2∘C for 3 h or using the stored thermal energy by discharging the device for 3 h. Favourable results were found for both options, where a BEFI of up to 47 kW (96%) is achieved. The proposed methodology for modeling and evaluation of control strategies is suitable for other similar convectively conditioned buildings equipped with active and passive storage.

scholarly journals Data-Driven Predictive Control of Building Energy Consumption under the IoT Architecture

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Ji Ke ◽  
Yude Qin ◽  
Biao Wang ◽  
Shundong Yang ◽  
Hao Wu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Management ◽  
Predictive Control ◽  
Control Strategies ◽  
Principal Component ◽  
Building Energy ◽  
Physical Models ◽  
Data Driven ◽  
Building Energy Management

Model predictive control is theoretically suitable for optimal control of the building, which provides a framework for optimizing a given cost function (e.g., energy consumption) subject to constraints (e.g., thermal comfort violations and HVAC system limitations) over the prediction horizon. However, due to the buildings’ heterogeneous nature, control-oriented physical models’ development may be cost and time prohibitive. Data-driven predictive control, integration of the “Internet of Things”, provides an attempt to bypass the need for physical modeling. This work presents an innovative study on a data-driven predictive control (DPC) for building energy management under the four-tier building energy Internet of Things architecture. Here, we develop a cloud-based SCADA building energy management system framework for the standardization of communication protocols and data formats, which is favorable for advanced control strategies implementation. Two DPC strategies based on building predictive models using the regression tree (RT) and the least-squares boosting (LSBoost) algorithms are presented, which are highly interpretable and easy for different stakeholders (end-user, building energy manager, and/or operator) to operate. The predictive model’s complexity is reduced by efficient feature selection to decrease the variables’ dimensionality and further alleviate the DPC optimization problem’s complexity. The selection is dependent on the principal component analysis (PCA) and the importance of disturbance variables (IoD). The proposed strategies are demonstrated both in residential and office buildings. The results show that the DPC-LSBoost has outperformed the DPC-RT and other existing control strategies (MPC, TDNN) in performance, scalability, and robustness.

Advances in Near-Optimal Control of Passive Building Thermal Storage

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Gregor P. Henze ◽  
Anthony R. Florita ◽  
Michael J. Brandemuehl ◽  
Clemens Felsmann ◽  
Hwakong Cheng
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Thermal Storage ◽  
Thermal Mass ◽  
Commercial Building ◽  
Simulation And Optimization ◽  
Rate Structure ◽  
Starting Point ◽  
Utility Rate ◽  
And Control

Using a simulation and optimization environment, this paper presents advances toward near-optimal building thermal mass control derived from full factorial analyses of the important parameters influencing the passive thermal storage process for a range of buildings and climate/utility rate structure combinations. Guidelines for the application of, and expected savings from, building thermal mass control strategies that can be easily implemented and result in a significant reduction in building operating costs and peak electrical demand are sought. In response to the actual utility rates imposed in the investigated cities, fundamental insights and control simplifications are derived from those buildings deemed suitable candidates. The near-optimal strategies are derived from the optimal control trajectory, consisting of four variables, and then tested for effectiveness and validated with respect to uncertainty regarding building parameters and climate variations. Due to the overriding impact of the utility rate structure on both savings and control strategy, combined with the overwhelming diversity of utility rates offered to commercial building customers, this study cannot offer universally valid control guidelines. Nevertheless, a significant number of cases, i.e., combinations of buildings, weather, and utility rate structure, have been investigated, which offer both insights and recommendations for simplified control strategies. These guidelines represent a good starting point for experimentation with building thermal mass control for a substantial range of building types, equipments, climates, and utility rates.

Advances in Near-Optimal Control of Passive Building Thermal Storage

2009 ◽  
Author(s):  
Gregor P. Henze ◽  
Anthony R. Florita ◽  
Michael J. Brandemuehl ◽  
Clemens Felsmann ◽  
Hwakong Cheng
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Thermal Storage ◽  
Thermal Mass ◽  
Commercial Building ◽  
Simulation And Optimization ◽  
Rate Structure ◽  
Starting Point ◽  
Utility Rate ◽  
And Control

Using a simulation and optimization environment, this paper presents advances towards near-optimal building thermal mass control derived from full factorial analyses of the important parameters influencing the passive thermal storage process for a range of buildings and climate/utility rate structure combinations. Guidelines for the application of, and expected savings from, building thermal mass control strategies that can be easily implemented and result in a significant reduction in building operating costs and peak electrical demand are sought. In response to the actual utility rates imposed in the investigated cities, fundamental insights and control simplifications are derived from those buildings deemed suitable candidates. The near-optimal strategies are derived from the optimal control trajectory, consisting of four variables, and then tested for effectiveness and validated with respect to uncertainty regarding building parameters and climate variations. Due to the overriding impact of the utility rate structure on both savings and control strategy, combined with the overwhelming diversity of utility rates offered to commercial building customers, the study cannot offer universally valid control guidelines. Nevertheless, a significant number of cases, i.e. combinations of buildings, weather, and utility rate structure, have been investigated, which offer both insight and recommendations for simplified control strategies. These guidelines represent a good starting point for experimentation with building thermal mass control for a substantial range of building types, equipment, climates, and utility rates.

A comparison of predictive control strategies for a highly segmented injection mold tempering

Polymer ◽  
2021 ◽  
Vol 218 ◽  
pp. 123494
Author(s):  
Ch. Hopmann ◽  
C.E. Kahve ◽  
M. Schmitz ◽  
M. Röbig
Keyword(s):  
Predictive Control ◽  
Control Strategies ◽  
Injection Mold

scholarly journals Special Issue “Advanced Phase Change Materials for Thermal Storage”

2021 ◽  
Vol 11 (4) ◽  
pp. 1390
Author(s):  
Rocío Bayón
Keyword(s):  
Energy Storage ◽  
Phase Change ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Phase Change Materials ◽  
Thermal Storage ◽  
Research Topic ◽  
Special Issue ◽  
Advanced Phase

Thermal energy storage using phase change materials (PCMs) is a research topic that has attracted much attention in recent decades [...]

scholarly journals Stratification Analysis and Behaviour of a Real Industrial Thermocline Thermal Energy Storage Tank for Cogeneration Purposes

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 120
Author(s):  
Francisco Fernández ◽  
José Díaz ◽  
María Folgueras ◽  
Inés Suárez
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Control Strategies ◽  
Storage System ◽  
Good Control ◽  
Energy Storage System ◽  
Temperature Gradients ◽  
Operation Conditions ◽  
Mean Temperature

Thermal energy storage systems help to couple thermal energy generation and process demand in cogeneration facilities. One single deposit with two design temperatures and one main temperature step in sensible thermal energy storage define the thermocline systems. Performance of one high size real thermocline thermal energy storage system is analysed. Starting from temperature and mass flow rate data registered by the plant control system, one advanced thermodynamic analysis is performed. The quality of heat storage is analysed in terms of evaluation of the stratification in the thermocline zone. The temperature data registered at 21 positions is extended by displacement analysis generating detailed profiles. Fraction of recoverable heat, thermocline width, stratification indices based on energy and exergy analysis, and mean temperature gradients in the thermocline region are calculated. These parameters are monitored under real operation conditions of the plant. The calculated parameters are studied to check their distribution and correlation. First and Second Law indices show parallel behaviour and two values are found that delimit situations of high and low values of mean temperature gradients. It was observed that buoyancy generates uniform forced movement with the right water temperature entering the diffusers, but good control strategies are essential to avoid mixing. The system demonstrated great stability in this use.

scholarly journals The Impact Assessment of Climate Change on Building Energy Consumption in Poland

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4084
Author(s):  
Hassan Bazazzadeh ◽  
Peiman Pilechiha ◽  
Adam Nadolny ◽  
Mohammadjavad Mahdavinejad ◽  
Seyedeh sara Hashemi safaei
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Thermal Load ◽  
Building Energy ◽  
Building Energy Consumption ◽  
Building Sector ◽  
Energy Demands ◽  
Heating Load ◽  
The Impact ◽  
The City

A substantial share of the building sector in global energy demand has attracted scholars to focus on the energy efficiency of the building sector. The building’s energy consumption has been projected to increase due to mass urbanization, high living comfort standards, and, more importantly, climate change. While climate change has potential impacts on the rate of energy consumption in buildings, several studies have shown that these impacts differ from one region to another. In response, this paper aimed to investigate the impact of climate change on the heating and cooling energy demands of buildings as influential variables in building energy consumption in the city of Poznan, Poland. In this sense, through the statistical downscaling method and considering the most recent Typical Meteorological Year (2004–2018) as the baseline, the future weather data for 2050 and 2080 of the city of Poznan were produced according to the HadCM3 and A2 GHG scenario. These generated files were then used to simulate the energy demands in 16 building prototypes of the ASHRAE 90.1 standard. The results indicate an average increase in cooling load and a decrease in heating load at 135% and 40% , respectively, by 2080. Due to the higher share of heating load, the total thermal load of the buildings decreased within the study period. Therefore, while the total thermal load is currently under the decrease, to avoid its rise in the future, serious measures should be taken to control the increased cooling demand and, consequently, thermal load and GHG emissions.

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