Dynamic Energy Models Research Articles

Integrative Review-Based Conceptual Modeling: An Agent-Based Modeling Synthesis of Dynamic Energy Tariff Research and Models

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it.

The effect of different subgrid-scale models on the flow field in cyclone separator using large-eddy simulations: A benchmark study

Abstract The cyclone separator is extensively utilized across industries to extract solid particles from gas streams. This study is focused on the steady and unsteady simulations of the Stairmand cyclone using large-eddy simulations aiming to assess the performance using different subgrid-scale models viz. standard Smagorinsky (Cs =1), dynamic Smagorinsky, Wall-Adapting Local Eddy-Viscosity (WALE), Wall-Modeled LES (WMLES), and dynamic kinetic energy models. The velocity profiles within the cyclone separator were analyzed under both steady and unsteady conditions, with reference to the Hoekstra experiment for validation and comparison. Velocity profiles inside the cyclone separator were inadequately predicted by the steady-state simulation, whereas the unsteady-state simulation yielded results more aligned with experimental values. The present study suggests that adopting subgrid-scale LES models such as standard Smagorinsky and WMLES offers a better option for analyzing flow patterns.

Scenarios for the energy renovation of a residential building

In this paper, the results of the energy renovation of a residential building, aimed at introducing it into a Renewable Energy Community (CER), are presented. A case study located in Florence (Italy) is discussed. Static and dynamic energy models have been used to evaluate the energy performance of the building, to compare different scenarios based on heat pumps (independent or centralised generator) and to evaluate them under the perspective of EPBD parameters. A comparison has been made concerning energy consumption and CO2 emissions. In its current state, the building presents an energy performance index of 129.8 kWh/(m2year) (class D). The energy refurbishment with heat pump (A4, 24.7 kWh/(m2year)) and VMC system (A4, 39.3 kWh/(m2year)) ensures a strong reduction in CO2 emissions, respectively 5.5 kg/(m2year) and 8.7 kg/(m2year) against 24.4 kg/(m2year) with the current gas fired boiler. The centralized heat pump configuration allows to further reduce the energy consumption. With the same thermal energy requirement, the results show a reduction of 14% of the power needs (without total recovery), thanks to the better sizing of the generator. Furthermore, the centralized heat pump opens a perspective of direct self-consumption of the energy product by the photovoltaic system into a CER configuration. The paper shows that the energy renovation with a heat pump is an effective way to reach the EPBD objectives and decarbonize the residential heating and cooling sector.

Preface

The 2022 International Conference on Advanced Materials and Chemical Engineering (AMCE 2022) was successfully held on 16-18 September, 2022 in Maoming, China (online conference). AMCE 2022 created a platform for experts, scholars, and engineers to share research findings and cutting-edge technologies, and gain an understanding of academic trends, fostering cooperation and transformation of academic outcomes.We were greatly honored to have Prof. Rujin Zhou from Guangdong University of Petrochemical Technology, China to serve as our Conference General Chair. There were 100 individuals attending the conference. Divided into three parts, the conference agenda covered keynote speeches, oral presentations, and online Q&A discussion. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers selected were presented by their authors by turns.During the conference, nine sophisticated professors were invited to address their keynote speeches. Among them, Prof. Saidur Rahman from Sunway University, Malaysia delivered a speech on the topic: Emerging Nano-materials in Heat Transfer Applications. His team was the first in Malaysia who successfully synthesized this new material using state of art lab equipment available in Research Centre for Nano-Materials and Energy Technology (RCNMET), Sunway University. He introduced to us about the emerging nano-materials and its various capabilities and explored the heat transfer behavior of MXene in solar energy applications. Additionally, Assoc. Prof. Muhyiddine Jradi from University of Southern Denmark, Denmark gave a report on: Research on Phase Change Materials (PCMs)-enhanced Building Envelope for Improved Thermal Comfort and Energy Efficiency. This presentation presented and evaluated PCM-enhanced building envelope under Danish conditions, simulated the impact of PCM integration on Dynamic energy models, and introduced the impact on the energy consumption, energy capacity, and thermal comfort. Their wonderful and dramatic speeches had triggered heated discussion. Moreover, every participant praised this conference for disseminating useful and insightful knowledge.After months of well preparation and hard work, the proceedings of AMCE 2022 covering a bunch of papers are smoothly published. These papers feature but are not limited to the following topics: Magnetic Materials, New Building Materials, Artificial Band Gap Materials, Colloid and Interface Chemistry, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.On behalf of the organizing committee, we would like to express our heartfelt appreciation to all the keynote speakers, peer reviewers, and all the participants. Particularly, we would like to acknowledge the Journal of Physics: Conference Series, for the endeavor of all its colleagues in publishing this paper volume. We firmly believe that all the attendees have had fruitful discussions and gained valuable knowledge, and will enjoy the opportunity for future collaborations.The Committee of AMCE 2022List of Committee member is available in the Pdf.

Towards large-scale simulation of indoor thermal conditions in buildings supplied with district heating: model evaluation based on experimental data

Utility companies are studying ways to improve the energy efficiency of district heating networks and promote flexible solutions. However, the impact of any modification must be verified, especially when dealing with existing buildings whose heating systems were originally sized based on different design conditions. Predictive simulations are carried out for this scope. Several building energy simulation options are available, computational effort and availability of input data being the strictest constraints for their adoption. In this preliminary work, real temperature measurements from a multi-family house in a demo site supplied by an experimental district heating branch have been used to assess the performances of dynamic energy models of different complexity. Images, local registries and literature studies have been used as sources of input information. Despite the high degree of approximation of the available data, encouraging results are found, with a root mean squared error below 1.5 °C over the heating season for a single dwelling, while inertial effects need to be better modelled when the whole building is simulated. The opportunity of improving the consistency and coordination between public databases is also discussed as a way to increase energy mapping possibilities.

Transient Modeling and Simulation of a Multiple‐Stage Evaporator in the Paper Industry

AbstractThe present work investigates the energy performance analysis of a heptad‐based multiple‐stage evaporator (MSE) under steady and transient conditions, integrated with different energy reduction schemes (such as steam split, feed split, and feed preheater). The steady‐state analysis was performed to optimize the steam economy subjected to the developed steady‐state energy models as the equality constraints. The simulated optimization is a maximization problem and is solved by Interior‐Point Optimizer and Gray Wolf Optimizer on two different platforms, GAMS and MATLAB, respectively. Further, transient and stability analyses were performed by developing and representing the nonlinear dynamic energy models to the state‐space representation using linearization.

Validation and calibration of dynamic energy models: energy audit of a public building

Detailed buildings energy audits require dynamic simulation models based on hourly input data. This paper presents the calibration and validation of an office building energy model for the heating and cooling services. Simulation are carried out by DesignBuilder software. Measured hourly heating and cooling energy supplied by the generation system are used for the calibration of the model. Employee behaviour with reference to occupancy profiles and indoor temperature settings is also considered. A good agreement between measured and simulated data is obtained for both heating and cooling seasons.

Research on the transient stability of HVDC rectifier-side AC system during the whole process of DC restart failure

HVDC restart failure can cause the DC power interruption, which may further result in the transient power angle of the rectifier-side AC system to go unstable. Concerning this problem, a transient stability analysis method considering dynamic changes of converter topologies during the whole process of the DC restart failure is proposed. First, dynamic energy models of the DC terminal and the AC filter in the whole process of the DC line restart failure are built, including the ‘restart at fault’, phase-shifted triggering and deionization stage. On this basis, according to the Lyapunov’s second theorem, the variation rate of the aperiodic component of generator dynamic energy is defined as the dissipation rate of dynamic energy, which characterizes the accumulation or the consumption trend of total system energy. Thus the stability of the system is assessed according to the dissipation rate of dynamic energy. Then, effects of the dynamic energy of the DC terminal and the AC filter on the dissipation rate of dynamic energy in the whole process of DC restart failure are illustrated, and the cause of the transient instability of the rectifier-side AC system is revealed. Finally, hardware-in-the-loop tests in RT-LAB verify that, when the amplitude of the generator outlet bus voltage rises during the ‘restart at fault’ and phase-shifted triggering stages, the dynamic energy of the DC terminal has a positive effect on the dissipation rate of dynamic energy, induces the total system energy to keep accumulating, which is not conducive for the stability of the system. In the deionization stage, the dynamic energy of the AC filter has a positive effect on the dissipation rate of dynamic energy, which is not conducive for the stability of system.

Comparison of Different Solutions for a Seismic and Energy Retrofit of an Auditorium

The increasing attention paid to climate change has boosted scientific research in the matter of energy refurbishment of existing public buildings. However, the design of the intervention must be integrated with structural upgrading when the constructions are located in seismic zones. Indeed, in Italy, as in other seismically active countries, the structural damage, observed after earthquakes, underlines the increase in economic losses for buildings retrofitted only for energy saving. In this framework, the paper introduces an integrated approach for selecting retrofit actions aimed at improving both the seismic and energy performance, starting from a detailed in situ analysis with which dynamic energy and structural simulation models are constructed. The case study is an auditorium erected in 1982 with a reinforced concrete structure inside a masonry ring wall of an ancient building. A step-by-step analysis of each component role in the structural and energy performance of the building is proposed. The results indicate that the proposed approach can help to determine the best technical solution, and the integrated design leads to saving 10% of the cost of the works.

Adaptive predictive control for peripheral equipment management to enhance energy efficiency in smart manufacturing systems

The importance of implementing energy efficiency methodologies in industrial environments has increased considerably in the last decade given the high energy costs and environmental impact (e.g., greenhouse gas emissions). This paper proposes a methodology to improve the energy efficiency of an industrial machine, without sacrificing either production or quality, using an adaptive predictive controller based on dynamic energy models that manages peripheral devices to activate/deactivate them at the proper times. The proposed adaptive mechanism aggregates robustness to the control system in industrial environments, which experiment constantly changes related to equipment degradation and that affect their energy consumption profile over time. Thus, this novel adaptive mechanism automatically updates the energy model to minimize the error between prediction and real energy consumption, including new energy behavior resulting from machine degradation. This methodology has been validated via a testbed and its performance was compared with rule-based control, which is the most widely used control strategy in industry. The energy efficiency of both approaches was evaluated using performance indicators, which show the effectiveness of the proposed control approach, highlighting remarkable improvements in reducing both energy consumption (about 2%) and sudden power peaks (more than 11%).

ENERGY ASSESSMENT OF URBAN BUILDINGS BASED ON GEOGRAPHIC INFORMATION SYSTEM

ABSTRACTUrban building energy analysis has attracted more attention as the population living in cities increases as does the associated energy consumption in urban environments. This paper proposes a systematic bottom-up method to conduct energy analysis and assess energy saving potentials by combining dynamic engineering-based energy models, machine learning models, and global sensitivity analysis within the GIS (Geographic Information System) environment for large-scale urban buildings. This method includes five steps: database construction of building parameters, automation of creating building models at the GIS environment, construction of machine learning models for building energy assessment, sensitivity analysis for choosing energy saving measures, and GIS visual evaluation of energy saving schemes. Campus buildings in Tianjin (China) are used as a case study to demonstrate the application of the method proposed in this research. The results indicate that the method proposed here can provide reliable and fast analysis to evaluate the energy performance of urban buildings and determine effective energy saving measures to reduce energy consumption of urban buildings. Moreover, the GIS-based analysis is very useful to both create energy models of buildings and display energy analysis results for urban buildings.

Uncertainty calibration of building energy models by combining approximate Bayesian computation and machine learning algorithms

Bayesian analysis has attracted more attention in calibrating building energy models since it can naturally account for uncertainty of input parameters. However, standard Bayesian analysis requires to compute likelihood functions to represent the probability of the observed data under a statistical energy model. This makes the implementation of standard Bayesian analysis difficult for calibrating dynamic building energy models. Therefore, this research proposes a new Bayesian method by combining the approximate Bayesian computation with machine learning techniques in calibrating building models without computing likelihood functions. The results indicate that this new Bayesian computation approach combined with the machine learning algorithms can provide fast and reliable calibration for building energy models created using the EnergyPlus program. The calibration metrics in terms of the coefficient variations of root mean square errors from this new Bayesian method are well below the threshold value (15%) recommended from the ASHRAE standard for monthly energy data. Moreover, the better calibration results can be obtained by using linear or nonlinear post-adjustment techniques to account for the differences between the simulated and observed energy data. The method proposed here can significantly extend the application of Bayesian analysis in calibrating building energy models under uncertainty due to its simplicity and fast computation. Furthermore, the new Bayesian approach combined with machine learning technique can also be used to calibrate the simulation-based models for various types of energy systems.

A method for the retrofitting of pre-1914 Walloon dwellings with heritage value

The sustainable energy renovation of historical buildings and listed heritage is a challenge for Belgium and other European countries. These are crucial for urban and rural development and for the future of old buildings. This is the context of the ‘P-RENEWAL’ research project. It aims to develop a methodological tool for retrofitting historical Walloon dwellings built before 1914, to enhance their heritage values while implementing relevant energy measures. The originality of this research is to consider energy, environmental and heritage aspects in a complementary way, in order to help designers achieving a goal of greater sustainability. According to the listed heritage administration, dwelling types built before 1914 represent approximately 25 % of the Walloon stock. This project is related to the research work carried out under the Task 59 of SHC ‘Renovating Historic Buildings Towards Zero Energy’. The methodology used to achieve the research objectives is articulated in various steps. First, a typological analysis of buildings from the interest era is completed. Then, based on on-site studies performed on representative case studies, the evaluations of heritage values and performance are conducted. Finally, dynamic energy models are run to support the proposition and validation of retrofitting strategies.

DanRETRO: A Decision-Making Tool for Energy Retrofit Design and Assessment of Danish Buildings

The building sector contributes a substantial amount to the overall energy consumption worldwide along with a large share in the corresponding greenhouse gas emissions. Thus, improving the performance of buildings is vital to achieve the energy and environmental goals. In this regard, Denmark is not an exception, where the building sector was prioritized, aiming to enhance newly-built buildings’ performance along with upgrading existing buildings through a comprehensive energy retrofit strategy. This study aims to present and demonstrate a decision-making tool for energy retrofit design and assessment of Danish buildings (DanRETRO). Unlike the current energy retrofit assessment methodologies and tools used in the Danish building market, DanRETRO builds on a database comprising a large number of simulations for Danish buildings’ performances of various types, sizes, and ages. The well-established modeling and simulation engine of EnergyPlus is used to develop the dynamic energy models. The DanRETRO tool development is presented, where multiple building retrofitting techniques and measures are carried out along with assessment of the impacts of implementing these improvements on the technical, economic, and environmental levels. The tool’s demonstration in three case study buildings is presented, where the retrofit assessment results are reported and evaluated at various levels.

Development of a Calibrated Simulation Method for Airborne Particles to Optimize Energy Consumption in Operating Rooms

Operating rooms are stringent controlled environments. All influential factors, in particular, airborne particles, must be within the limits established by regulations. Therefore, energy efficiency stays in the background, prioritizing safety and comfort in surgical areas. However, the potential of improvement in energy savings without compromising this safety is broad. This work presents a new procedure, based on calibrated simulations, that allows the identification of potential energy savings in an operating room, complying with current airborne particle standards. Dynamic energy and airborne particle models are developed and then simulated in TRNSYS and calibrated with GenOpt. The methodology is validated through experimental contrast with a real operating room of a hospital in Spain. A calibrated model with around 2% of error is achieved. The procedure determines the variation in particle concentration according to the flow rate of ventilation supplied and the occupancy of the operating room. In conclusion, energy savings up to 51% are possible, reducing ventilation by 50% while complying with airborne particles standards.

Apparent delay analysis for a flat-plate solar field model designed for control purposes

This study presents an analysis of the effect of the transport delay which occurs in solar flat-plate collector fields and how to include its behavior in dynamic models suitable for control purposes. This investigation has been carried out using simplified models based on dynamic energy balances and models based on step response methods and experimental tests. The solar flat-plate collector field encompasses parallel absorber pipes intertwined with pipelines which act as several first-order plus dead time systems in parallel. The effect is an apparent delay observed at the outlet temperature that must be included in the dynamic model in order to reduce the error between the real measurement and the model prediction. The main contribution of this paper is the procedure to evaluate the apparent delay to obtain adequate dynamic models aimed to be used for control purposes.

Comparison of dynamic urban building energy models (UBEM): Sigmoid energy signature and physical modelling approach

Thermal energy demand represents over 30% of overall energy consumption and thus is a vital target for the decarbonisation of our energy supply. This fact is the reason why dynamic thermal modelling of buildings, components and infrastructure has been gaining increasing importance in the context of the transformation of existing energy systems into smart energy systems. For the first time, this study presents a comparison of two major bottom-up approaches to modelling urban neighbourhoods: a physical modelling approach and a data-driven approach. The physical method is represented by a GIS-based automated modelling approach with detailed dynamic building simulation in IDA ICE. In the data-driven approach, an energy signature is applied, which uses a non-linear data-driven method. These two methods were validated on the basis of a multi-family house, an office building and a residential area with 34 buildings by means of detailed multi-zone building simulation and measurement data. The simulation results show that both applied approaches are applicable in these cases within good agreement compared to the measurement data (physical/data-driven: multi-family house (RN_RMSE(%) = 14.7/9.3; R2 = 0.68/0.87), office building (RN_RMSE(%) = 7.6/5.4; R2 = 0.92/0.96) and residential area (RN_RMSE(%) = 8.2/4.8; R2 = 0.92/0.97)). Finally, the fields of application of both approaches are discussed. A major finding here is that the energy signature shows slightly better results at deriving the load profile when the measured heating demand is present from a previous heating season. Furthermore, the number of buildings does not affect the duration of a simulation because cumulative user profiles are used. Whereas the simulation duration of the physical approach depends essentially on the size of the investigated area. The physical approaches have the advantage of being able to include densification or renovation scenarios, demand forecasting and coupled simulations of buildings and smart energy systems of neighbourhoods.

Energy efficiency facets: innovative district cooling systems

Cooling demand in buildings is globally increasing, therefore developing more efficient cooling systems is important for the sustainability of European cities. Directive 2012/27/EU of the European Parliament and of the council on energy efficiency states: “Member States should carry out a comprehensive assessment of the potential for high-efficiency cogeneration and district heating and cooling†. The EU project INDIGO is investigating this issue considering also the economic efficiency and the use of renewable energy sources. In a district cooling system different kinds of cooling production can be combined. E.g., the use of absorption chillers with waste heat or through the solar cooling or the use of free cooling (generally the heat is rejected to seas, lakes, rivers or waterways) offer the possibility of a more sustainable way of cooling. Controlling those systems in an efficient way is a complex problem (consider that the cooling demand is much more difficult to predict than the heat demand, particularly the peaks, and sources such as the solar energy and the waste heat are not predetermined by the designers). The main results of INDIGO will be the development of: - predictive controllers (responsible for obtaining the HVAC systems set-points and based on component dynamic thermos-fluid models, some of them also including embedded self-learning algorithms); - system management algorithms (focused on energy efficiency maximization or energy cost minimization); - an open-source planning tool (based on design and performance parameters as well as simulation and optimisation results; LCA framework will be used as a method for both economic feasibility and climate impact assessment). To validate the results, the consortium is analysing case studies, both through energy modelling and through on-site observations and measurements. The present paper focuses mainly on the development of dynamic energy models and on their use in the context of the project.

Assessment of linear emulators in lightweight Bayesian calibration of dynamic building energy models for parameter estimation and performance prediction

Calibration of building energy models is widely used in building energy audits and retrofit practices. Li et al. (2015) proposed a lightweight approach for the Bayesian calibration of dynamic building energy models, which alleviate the computation issues by the use of a linear regression emulator. As a further extension, this paper has the following contributions. First, it provides a brief literature review that motivates the original work. Second, it explained the detailed calibration methodology and its mathematical formulas, and in addition the prediction using meta-models. Third, it introduced new performance metrics for evaluating predictive distributions under uncertainty. Fourth, it used the standard Bayesian calibration method as the benchmark, assessed the capability of regression emulators of different complexity, and showed the comparison result in a case study. Compared to the standard Gaussian process emulator, the linear regression emulator including main and interaction effects is much simpler both in interpretation and implementation, calibrations are performed much more quickly, and the calibration performances are similar. This indicates a capability to perform fast risk-conscious calibration for most current retrofit practice where only monthly consumption and demand data from utility bills are available.

Calibration of Dynamic Building Energy Models with Multiple Responses Using Bayesian Inference and Linear Regression Models

This paper proposes a lightweight Bayesian calibration of dynamic models that accounts for model parameter uncertainties. A regression model was built to represent the dynamic model using parameter screening and multiple linear regression. Given this regression model and prior probability distributions of its input parameters, a Bayesian calibration method is developed to provide their posterior distributions. A case study is presented and the result shows considerable alignment between model prediction and measurement after calibration. This indicates its capability to perform fast risk-conscious calibration for most current retrofit practice where only monthly consumption and demand data are available.