EnergyPlus Building Research Articles

Multi-objective optimization of building energy performance and indoor thermal comfort: A new method using artificial bee colony (ABC)

The aim of this paper is to present a powerful simulation-based multi-objective optimization of building energy efficiency and indoor thermal comfort to obtain the optimal solutions of the comfort-energy efficient configurations of building envelope. The optimization method is developed by integrating a multi-objective artificial bee colony (MOABC) optimization algorithm implemented in MATLAB with EnergyPlus building energy simulation tool. The proposed optimization approach is applied to a single office room; and the building parameters, including the room rotation, window size, cooling and heating setpoint temperatures, glazing and wall material properties are considered as decision variables. In the present study, single-objective and multi-objective optimization analyses of the total annual building electricity consumption and the Predicted Percentage of Dissatisfied (PPD) are investigated to bring down the total energy cost as well as the thermal discomfort in four major climate regions of Iran, i.e. temperate, warm-dry, warm-humid and cold ones. In the results part, the achieved optimal solutions are presented in the form of Pareto fronts to reveal the mutual impacts of variables on the building energy consumption and the thermal discomfort. Finally, the ultimate optimum solution on the Pareto fronts are selected by TOPSIS decision-making method and the results of double-objective minimization problem are compared with the single-objective ones as well as the base design. The results of double-objective optimization problem indicate that in different climates, even though the total building electricity consumption increases a bit about 2.9–11.3%, the PPD significantly decreases about 49.1–56.8% compared to the baseline model. In addition, the comparisons of single-objective and double-objective optimization approaches clearly show that multi-objective optimization methods yield more appropriate results respect to the single ones, mainly because of the lower deviation index value from the ideal solution.

The effect of time-of-use tariffs on the demand response flexibility of an all-electric smart-grid-ready dwelling

The paper is concerned with the development and evaluation of control algorithms for the implementation of demand response strategies in a smart-grid enabled all-electric residential building. The dwelling is equipped with a 12kW heat pump, a 0.8m3 water storage tank, a 6kW photovoltaic (PV) array, solar thermal collectors for domestic hot water heating and an electric vehicle. The building, located in Ireland, is fully instrumented. An EnergyPlus building simulation model of the dwelling was developed and calibrated using monitored data from the building. The developed model is used to assess the effectiveness of demand response strategies using different time-of-use electricity tariffs in conjunction with zone thermal control. A reduction in generation cost (−22.5%), electricity end-use expenditure (−4.9%) and carbon emission (−7.6%), were estimated when DR measures were implemented and compared with a baseline system. Furthermore, when the zone control features were enabled, the efficiency of the control improved significantly giving, an overall annual economic saving of 16.5% for the residential energy cost. The analysis also identified an annual reduction of consumer electricity consumption of up to 15.9%, lower carbon emissions of 27% and facilitated greater utilisation of electricity generated by grid-scale renewable resources, resulting in a reduction of generation costs for the utility of up to 45.3%.

A novel approach for the simulation-based optimization of the buildings energy consumption using NSGA-II: Case study in Iran

This paper provides a novel and efficient approach for the simulation-based multi-criteria optimization of the building energy performance. In the current investigation, a multi-objective non-dominated sorting genetic algorithm (NSGA-II) is coupled with EnergyPlus building energy simulation program to obtain optimal solutions leads to increase the building energy performance. The main aim of this work is to explore the effect of some architectural parameters, including the building orientation, the window size and the overhang specifications on the building energy consumption in four major climatic regions of Iran, e.g. cold, mild, warm-dry, and warm-humid. In the optimization section, mono-criterion and bi-criteria optimization analyses of the annual cooling and lighting building energy demands are studied with the purpose of understanding the interactions between these objective functions. The results point out that the bi-criteria optimization of the test case model brings down the annual cooling energy consumption 55.8–76.4% in various climates. However, the annual lighting electricity demand increases 1–4.8%. As a result, the final optimum configuration leads to 23.8–42.2% decrease in the annual total building energy consumption. The results depict that the climate and the appropriate selection of the architectural parameters are very important and critical in reducing the building energy consumption. The proposed optimization methodology is a powerful and useful tool to achieve this goal and to facilitate decision-making in early phases of a building design in order to enhance its energy efficiency.

Case Study of Multiple Regression as Evaluation Tool for the Study of Relationships between Energy Demand, Air Tightness, and Associated Factors

AbstractAddressing air leakage and its influencing factors in buildings is very important for further improvement of buildings’ energy efficiency. The evaluation of how energy use is influenced by the design parameters of buildings is also crucial for architects in early design stages when there is a need for rapid assessment of the effect of minor and major design changes in overall energy demand. This paper helps fill the information gap on predictive models for this field, which became evident during literature review. This work examines the relationship between energy demand, air-tightness, and their influencing factors including volume, treated floor area, building age, compactness, window-to-wall ratio, and frame-length factor of 18 dwellings constructed between 2005 and 2014 in Estonia. The buildings involved in the study are mostly energy-efficient buildings, e.g., there were two passive houses and one net-zero energy building that also qualifies as a plus-energy building. The paper employs the AN...

A Hybrid Physics-Based and Data Driven Approach to Optimal Control of Building Cooling/Heating Systems

This work integrates a physics-based model with a data driven time-series model to forecast and optimally manage building energy. Physical characterization of the building is partially captured by a collection of zonal energy balance equations with parameters estimated using a least squares estimation (LSE) technique and data initially generated from the EnergyPlus building model. A generalized Cochran–Orcutt estimation technique is adopted to describe the data generated from these simulations. The combined forecast model is then used in a model predictive control (MPC) framework to manage heating and cooling set points. This work is motivated by the practical limitations of simulation-based optimizations. Once the forecast model is established capturing sufficient statistical variability and physical behavior of the building, there will be no more need to run EnergyPlus in the optimization routine.

Energy performance evaluation of a net plus-energy residential building with grid-connected photovoltaic system in Brazil

The proposition of Net Plus-energy Buildings (NPEB) leads to the need to carry out studies of load matching in contrast with the grid impacts of distributed generation (DG). This paper performs simulations with the EnergyPlus software tool concerning a NPEB operating in four Brazilian metropolitan areas. The analyses include photovoltaic (PV) performance parameters and Load Matching and Grid Interaction indicators (LMGI). New grid impact indicators are defined in order to study the impacts of DG in the power grid. In the second stage, the work investigates economic aspects under net metering supporting. Results show the annual amount of electrical demand covered by PV varies from 29 to 51% with more potential in situations with higher PV production and higher cooling load, and the annual PV electricity that supplies the loads varies from 24 to 36% according to the seasonal variations of PV-load correlation. The levels of exported electricity into the grid are high in Brazil with annual mean power peaks surrounding 0.7 but can surpass 0.8 in the sunniest periods. The economy demonstrates the building achieves grid parity from 6 to 18% discount rates and the payback time is given for different scenarios of investment costs, discount rates and electricity tariffs.

Effect of Supermarket Refrigeration Systems on Water Consumption in California

ABSTRACTThis article examines the environmental impact of different commercial supermarket refrigeration systems on the energy and water consumption. The research uses industry standard EnergyPlus building models to compare the environmental impact of air and evaporative cooling methods for the condensers. The energy simulation covers all microclimate regions across California.

Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)

This paper proposes an efficient methodology for the simulation-based multi-objective optimization problems, which addresses important limitations for the optimization of the building energy performance. In this work, a mono- and multi-objective particle swarm optimization (MOPSO) algorithm is coupled with EnergyPlus building energy simulation software to find a set of non-dominated solutions to enhance the building energy performance. To evaluate the capability and effectiveness of the approach, the developed method is applied to a single room model, and the effect of building architectural parameters including, the building orientation, the shading overhang specifications, the window size, and the glazing and the wall material properties on the building energy consumption are studied in four major climatic regions of Iran. In the optimization section, mono-criterion and multi-criteria optimization analyses of the annual cooling, heating, and lighting electricity consumption are examined to understand interactions between the objective functions and to minimize the annual total building energy demand. The achieved optimum solutions from the multi-objective optimization process are also reported as Pareto optimal fronts. Finally, the result of multi-criteria minimization is compared with the mono-criterion ones. The results of the triple-objective optimization problem point out that for our typical model, the annual cooling electricity decreases about 19.8–33.3%; while the annual heating and lighting ones increase 1.7–4.8% and 0.5–2.6%, respectively, in comparison to the baseline model for four diverse climatic regions of Iran. In addition, the optimum design leads to 1.6–11.3% diminution of the total annual building electricity demand. The proposed optimization method shows a powerful and useful tool that can save time while searching for the optimal solutions with conflicting objective functions; therefore facilitate decision making in early phases of a building design in order to enhance its energy efficiency.

A new validation protocol for an urban microclimate model based on temperature measurements in a Central European city

In this paper, we provide further evidence of the reliability of a lumped parameter urban canopy model coupled with an EnergyPlus building energy model to estimate urban temperatures. In a previous paper, we presented a preliminary validation of the model using data measured at Masdar Institute, Abu Dhabi, United Arab Emirates. At present, we conduct a more comprehensive validation based on BUBBLE experimental data measured in the Sperrstrasse, a street canyon located in Basel downtown, Switzerland. To extend the coupled scheme for the Sperrstrasse and future work, we developed methods for approximating waste heat releases generated by a heating system, anthropogenic heat gains created by traffic, and direct normal solar irradiance. Based on a baseline coupled scheme model for the Sperrstrasse, we evaluate the sensitivity of urban temperature estimates to ±20% variations of each parameter. We finally show, through Monte-Carlo analysis, that the coupled scheme can achieve satisfactory accuracy in a dense Central European city.

The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis

The majority of decisions in the building design process are taken in the early design stage. This delicate phase presents the greatest opportunity to obtain high performance buildings, but pertinent performance information is needed for designers to be able to deal with multidisciplinary and contrasting objectives. In the present work, an integrative approach for the early stages of building design is proposed to obtain detailed information on energy efficient envelope configurations. By means of genetic algorithms, a multi-objective search was performed with the aim of minimising the energy need for heating, cooling and lighting of a case study. The investigation was carried out for an open space office building by varying number, position, shape and type of windows and the thickness of the masonry walls. The search was performed through an implementation of the NSGA-II algorithm, which was made capable of exchanging information with the EnergyPlus building energy simulation tool. The analyses were conducted both in absence and in presence of an urban context in the climates of Palermo, Torino, Frankfurt and Oslo. In addition, a preliminary analysis on the Pareto front solutions was performed to investigate the statistical variation of the values assumed by the input variables in all the non-dominated solutions. For the analysed case study, results highlighted a small overall Window-to-Wall Ratio (WWR) of the building in all locations. Pareto front solutions were characterised by low WWR values especially in east, west and north exposed facades. The area of the south facing windows was higher compared to the other orientations and characterised by a higher variability.

Assessment of the Potential to Achieve very Low Energy Use in Public Buildings in China with Advanced Window and Shading Systems

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the U.S. model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future. System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24%–66% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30%–80% reductions in perimeter zone HVAC electricity use in Beijing and 18%–38% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

Using the Big Bang – Big Crunch Algorithm for Rational Design of an Energy-Plus Building

Reduction of the energy consumption without compromising living standard has become very important issue in architecture, civil engineering and building industry. This problem includes numerous independent and often contradictory aspects. That indicates that a compromise between construction cost and energy efficiency should be found.The study presented in this paper has shown that choice of structural system and its elements can significantly influence the total price of a building as well its environmental impact. Since these two aspects are usually directly confronted, the decision-maker should be aware of all their advantages and disadvantages. Therefore, numerical analysis for exploring different possibilities should not be exclusive, i.e. not to provide only one solution, but to offer at least several solutions in order to enable decision-maker to get a good insight and to make the most appropriate choice considering given situation. The methodology presented in this paper, based on multi-objective Big Bang – Big Crunch algorithm, has proven to be successful in solving this kind of problem.

Energy and indoor air quality implications of alternative minimum ventilation rates in California offices

The energy and IAQ implications of varying prescribed minimum outdoor air ventilation rates (VRs) in California office buildings were estimated using the EnergyPlus building simulation software tool. Weighting factors were used to scale these model predictions to state wide estimates. Energy use predictions were then verified using surveyed California building energy end use data.Models predicted state wide office electricity use that was within 15% of reported electricity consumption from power utilities. The HVAC energy penalty of providing the current Title-24 VRs was approximately 6%, of the total HVAC energy use. Having economizers installed reduced average indoor formaldehyde exposure by 38% and lowered HVAC EUI by 20%. For California offices with economizers, 50% and 100% increases in Title-24 prescribed minimum VRs increased heating, ventilating, and air conditioning (HVAC) modeled energy use by 7.6% and 21.6%, respectively, while decreasing the annual average workplace formaldehyde exposure by 8.6% and 14.4%, respectively. Economizers increased VRs above the minimum 79% of the time lowering annual average concentrations of formaldehyde. Decreasing minimum VRs below the Title-24 rate would have smaller predicted effects on energy use and comparatively larger effects on formaldehyde concentrations. In buildings without economizers in many climate zones, increasing VRs up to 150% of the current Title-24 minimum would save HVAC energy and significantly reduce formaldehyde.A key conclusion is that raising future minimum VRs in California offices is unlikely to significantly improve time-averaged IAQ in buildings with economizers. Lowering future minimum VRs would be unlikely to deliver substantive energy savings.

Research on the Design and Construction of Zero-Energy Building

A zero-energy building, also known as a zero net energy (ZNE) building, net-zero energy building (NZEB), or net zero building, is a building with zero net energy consumption and zero carbon emissions annually. Buildings that produce a surplus of energy over the year may be called “energy-plus buildings” and buildings that consume slightly more energy than they produce are called “near-zero energy buildings” or “ultra-low energy houses”. Traditional buildings consume 40% of the total fossil fuel energy in the US and European Union and are significant contributors of greenhouse gases. The zero net energy consumption principle is viewed as a means to reduce carbon emissions and reduce dependence on fossil fuels and although zero energy buildings remain uncommon even in developed countries, they are gaining importance and popularity.

Improving the capabilities of the Town Energy Balance model with up-to-date building energy simulation algorithms: an application to a set of representative buildings in Paris

Abstract Buildings’ energy systems release heat to the atmosphere that contributes to the urban heat island. In return, the energy demand from buildings depends on the meteorological conditions of their surroundings. Consequently, urban canopy models such as Town Energy Budget (TEB) have progressively included the representation of the main processes of building energetics: solar and internal heat gains, heat transmission through the enclosure and the heat exchange by infiltration and ventilation. The objective of this study is to extend the evaluation of the Building Energy Model (BEM) implemented in TEB. Five buildings representative of the morphological and thermal characteristics that can be encountered in European urban areas have been selected. The evaluation has been conducted with EnergyPlus building energy model and for two contrasted climates. The TEB model is able to estimate the heating and the cooling energy demand with an accuracy better than 5 kWh/m 2 /year for heating and 3 kWh/m 2 /year for cooling. This paper also discusses on the importance of computing the building's surrounding surface temperature for energy demand calculations. TEB is able to account for this effect whereas EnergyPlus assumes that building surroundings are at air temperature.

Energy performance enhancement in multistory residential buildings

This paper presents a study of energy performance enhancement methods in multistory residential buildings. The study is carried out for Montreal location, Canada (45°N). All configurations considered assume a suburban environment that allows high solar exposure and no obstruction from adjacent buildings or external surrounding objects such as trees. Energy performance is measured by the balance between energy consumption, on the demand side, and electricity production by means of integrated PV systems, on the supply side. The present study considers enhancement of the supply side by increasing electricity generation potential.Apartment buildings are designed to be highly energy efficient and to conform to passive solar design principles. The buildings investigated include – low rise (3–5 floors), mid-rise (6–9 floors) and high-rise (up to 12 floors), with eight apartments per floor. All Integration of PV systems in façades, in addition to roof surfaces, is considered, in view of the reduced availability of roof surface per dwelling unit. The results of simulations employing the EnergyPlus building simulation program indicate that apartment buildings are relatively energy efficient for heating and cooling, while allowing a high level of residential density, but their solar potential is limited. Under the present study, a building of three stories can generate about 96% of its total energy use, if the roof design is optimized for solar energy generation. Above 3 floors, additional measures are required to enhance energy production. Implementing PV systems on 50% of south façade and 80% of east and west façades surface areas, in addition to enhanced roof surface design (folded-plate), enables electricity production of up to 90% of energy use of a 4-story building reducing with increasing height to 50% for 12 stories.The study indicates that investment in advanced design of façades (such as folded-plate curtain walls) can substantially increase electricity production and achieve net zero and surplus energy status in building over eight stories high.

Effects of load-following operational methods on combined heat and power system efficiency

Combined heat and power (CHP) systems can be operated in partial loading situations when the maximum electrical and thermal output of the prime mover is not constantly required by the facility. Two basic load-following methods following the thermal load (FTL) and following the electric load (FEL), are compared with a hybrid method which either follows the thermal or the electric demand in a given time period, within a specified operating range, in order to minimize the amount of excess electrical or thermal energy produced by the CHP system. These methods are implemented on an hour by hour basis for a large hotel benchmark building which is modeled in 16 cities located in different climate zones using EnergyPlus building simulation software. The hybrid method results in a higher total CHP system efficiency than either the FTL or FEL methods, with CHP system efficiency values from 71% to 87%. The power-to-heat ratio of the building (PHRb), which describes the relationship between electrical and thermal demand for the given facility, is found to predict the maximum possible CHP system efficiency using the hybrid method on an hourly basis. Buildings with lower PHRb values, corresponding to higher relative thermal demands, have the highest possible CHP system efficiency values. The hybrid operational method is also implemented on a monthly basis, where the building’s average monthly demands are used to set the operating condition of the prime mover for the entire month. The building is then simulated on an hour by hour basis to determine the system’s performance with only monthly changes in the loading conditions. This monthly method produces similar results to the hybrid method when it is implemented on an hourly basis, with CHP system efficiency values from 74% to 86%.

Planning and research of smart buildings and constructions with the ‘Energydesign Roadmap’ method

Due to negative environmental changes and the energy supply problems of the society the EPBD 2010/31/EU prescribes for EU member states to ensure that by 2021 all new buildings are nearly zero energy buildings. The Energydesign® research team of the University of Pécs has developed a research-design method applicable for building climate, energy, aerodynamic and architectural technology modeling of smart energy-plus buildings. This problem-solving matrix arranges the systematic structured planning process, calculations, complex analysis, dynamic energy-climate and computational fluid dynamics simulation control of buildings through a finite number of algorithmic steps. The description of the logged design steps is meant to be an instructional process-guide, the Energydesign Roadmap.

Classification of Commercial Building Electrical Demand Profiles for Energy Storage Applications

Commercial buildings have a significant impact on energy and the environment, being responsible for more than 18% of the annual primary energy consumption in the United States. Analyzing their electrical demand profiles is necessary for the assessment of supply-demand interactions and potential; of particular importance are supply- or demand-side energy storage assets and the value they bring to various stakeholders in the smart grid context. This research developed and applied unsupervised classification of commercial buildings according to their electrical demand profile. A Department of Energy (DOE) database was employed, containing electrical demand profiles representing the United States commercial building stock as detailed in the 2003 Commercial Buildings Consumption Survey (CBECS) and as modeled in the EnergyPlus building energy simulation tool. The essence of the approach was: (1) discrete wavelet transformation of the electrical demand profiles, (2) energy and entropy feature extraction (absolute and relative) from the wavelet levels at definitive time frames, and (3) Bayesian probabilistic hierarchical clustering of the features to classify the buildings in terms of similar patterns of electrical demand. The process yielded a categorized and more manageable set of representative electrical demand profiles, inference of the characteristics influencing supply-demand interactions, and a test bed for quantifying the impact of applying energy storage technologies.

An empirical study of a full-scale polymer thermochromic window and its implications on material science development objectives

Large-area polymer thermochromic (TC) laminated windows were evaluated in a full-scale testbed office. The TC interlayer film exhibited thermochromism through a ligand exchange process, producing a change in solar absorption primarily in the visible range while maintaining transparent, undistorted views through the material. The film had a broad switching temperature range and when combined to make an insulating window unit had center-of-glass properties of Tsol=0.12–0.03, Tvis=0.28–0.03 for a glass temperature range of 24–75°C. Field test measurements enabled characterization of switching as a function of incident solar irradiance and outdoor air temperature, illustrating how radiation influences glass temperature and thus effectively lowers the critical switching temperature of TC devices. This was further supported by EnergyPlus building energy simulations. Both empirical and simulation data were used to illustrate how the ideal critical switching temperature or temperature range for TC devices should be based on zone heat balance, not ambient air temperature. Annual energy use data are given to illustrate the energy savings potential of this type of thermochromic. Based on observations in the field, a broad switching temperature range was found to be useful in ensuring a uniform appearance when incident irradiance is non-uniform across the facade. As indicated in prior research, a high visible transmittance in both the switched and unswitched state is also desirable to enable reduction of lighting energy use and enhance indoor environmental quality.