Loads In Commercial Buildings Research Articles

Optimal energy management of Ice thermal energy storage-based air conditioning system for commercial buildings in real-time – A review based on POET framework

This paper applied the POET framework to analyze and identify possible energy efficiency activities that may reduce energy costs in HVAC cooling systems with Ice Thermal Energy Storage (ITES) in order to achieve maximum potential cost-savings, particularly for cooling loads in commercial buildings. Significant cost savings may be realized by the optimal shifting of the energy usage profile to the least costly regions of the Time-of-Use (TOU) using the ITES system. Moreover, a further reduction of energy costs may be achieved by introducing renewable energy (RE) sourced systems. A potential reduction of approximately 50% in energy cost savings could be achieved with the application of the POET framework. Improvement in operational efficiency may be achieved if systems were optimally sized and controlled. Studies conducted on control methods have shown that Model Predictive Control (MPC) offers significant benefits of achieving reasonable operational efficiency compared to other methods, particularly on HVAC systems. Combined ITES and hybrid energy systems allow an additional advantage in demand-side management, per the TOU tariff and peak demand. This may ultimately result in minimal energy usage during the costly regions of the TOU tariff, which would minimize energy costs and technology and equipment efficiency may be improved.

Curtain Wall with Solar Preheating of Ventilation Air. Full Scale Experimental Assessment

Heating load in Commercial buildings is highly related with ventilation systems, while at the same time local discomfort in the vicinity of glass walls occurs due to overheating. In this paper, a novel double envelope curtain wall is presented, which extracts heat from the façade by means of a ventilated cavity which is then incorporated to the ventilation air intake. A substantial reduction of heating loads is achieved. Whenever solar gains are not sought, a bypass element allows the natural ventilation of this air cavity, acting as a ventilated façade. An integrated control system with embedded electronics and actuators allows for a smart control of the system. The system is designed for integration with existing rooftop ventilation systems. Design considerations are discussed, and the outcomes of a full-scale experiment conducted in Bilbao (Spain) along 2019 presented.

A simplistic and efficient method of estimating air-conditioning load of commercial buildings in the sub-tropical climate

Energy efficiency of buildings is attracting significant attention from the research community, as the world is moving towards sustainable building designs. The average heat gain is the crucial measure for estimating the energy consumption of the buildings. The Envelope Thermal Transfer Value (ETTV) is a simplistic method of determining average heat gain in buildings through its envelopes considering all heat gain components. It also measures the energy efficiency of buildings without inhibiting the design options. The values of ETTV coefficients highly depend on the climatic conditions, geographical locations and the orientation of the buildings. However, no study has been done to investigate the suitability of applying ETTV approach and to develop ETTV formulations for extreme solar radiation with hot and windy climatic conditions like Australian environments. In addition to this, the relevant studies reported in the literature are not comprehensive enough as the coefficient were developed using limited data and the developed formulations were not applied to a variety of real buildings to validate them. Therefore, the main aim of this study is to develop the coefficients of envelope thermal transfer value for commercial buildings, formulate new ETTV equations for buildings with external shadings and estimate the ETTV based annual cooling energy in the sub-tropical climates of Australia. In this study, real life building data relevant to all heat gain parameters of five existing commercial building have been collected and hourly data of wall conduction, window conduction and solar radiation for 11 different types of wall construction and 54 types of window construction have been analysed to determine coefficients of ETTV. Based on these coefficients, the new formulation of ETTV has been proposed to determine total ETTV value of commercial buildings in sub-tropical climate. The developed formulations have been used to estimate the cooling energy loads of 10 real life buildings. A comparative study has been conducted between these estimated cooling energy consumption based on ETTV, actual building load and simulated cooling energy using commercial software. It was demonstrated that developed equations accurately estimate the building cooling load. The computed values of ETTV are within the range 24–42 W/m2, which can be applied in any air-conditioned commercial building in sub-tropical climate like Australia.

Effective management of plug loads in commercial buildings with occupant engagement and centralized controls

Plug loads, or devices plugged into wall outlets, comprise a growing proportion of commercial building electricity consumption. This study presents the results of a hybrid approach for plug load management, which includes a combination of occupant engagement and centralized controls. Electricity consumption was monitored for 249 plug load devices in the XFINITY Center at the University of Maryland. After a baseline monitoring period, 1) on-off schedules were set for 78 devices in the concession stands, and 2) 31 office occupants in the facility took part in an energy competition and were given access to a mobile energy app (Keewi, Inc.) to control their 115 devices. Centralized controls resulted in a reduction of 58% in consumption in the concessions during the days when the concessions were not in use. Occupant engagement led to a reduction of 32% in plug load electricity consumption in the offices. Savings were largest in high-consumption categories such as merchandisers and food preparation chillers in the concessions, and IT equipment, refrigerators, desktop computers, and space heaters in the offices. The study indicates the benefits of hybrid approaches to plug load management given unique facility characteristics.

Emergency frequency control by using heavy thermal conditioning loads in commercial buildings at smart grids

The power system frequency may be subjected to a severe drop without a balanced power between generation and load demand side. The emergency frequency control system traditionally depends on under-voltage and under-frequency load shedding techniques of power system feeders in cascading steps. As a result, the power systems suffer from a series of disturbances, leading to various degrees of blackouts. Traditional electric power grids are developed to be smarter, especially with control and protection issues underpinned by advanced measurement and communication technologies. Hence, this paper proposes a novel technique of wide-area frequency control. This control scheme depends on controlling thermal conditioning loads instead of disconnecting power system loads and comprises distributed multi-agents among wide-area system. The integration of advanced measurement system supported by new communication technologies and robust control algorithm is essential in this technique. MATLAB is used to simulate the wide-area frequency control model. The control technique is evaluated through incepting various kinds of disturbances on the new control model.

Reducing emissions from consumer energy storage using retail rate design

Minimizing retail electricity costs via demand charge management and energy arbitrage is a common application of behind-the-meter energy storage systems (ESS). Research suggests that ESS tend to increase grid emissions, but some speculate that retail rate design could lessen its impact. This paper tests that theory. In this analysis, we pair five years of historic data from ISO New England (ISO-NE) and the PJM Interconnection with 15 commercial building load profiles to reveal how different rate designs influence emissions from ESS.We find that demand and energy charges can be configured to lessen the emissions impact of ESS in some markets and reduce net system emissions in others. Minimizing different types of demand charges requires different quantities of ESS dispatch: some can be minimized in hours while others require days. Time-varying energy charges increase dispatch compared to flat charges because the ESS is used for demand charge management and energy arbitrage. Separately, time-varying energy charges reduce emissions per MW h-stored compared to flat charges, all else equal. Unfortunately, a rate design that minimizes emissions in one market might increase emissions if implemented in another. This confounds the creation of universal solutions and highlights the need for approaches tailored to specific markets.

Erratum to: A Bayesian Network model for predicting cooling load of commercial buildings

the HTML version of the article unfortunately the copyright holder is incorrect. It should be “© US Government (outside the USA) 2017”. It is correct in the PDF. The publisher apologizes for the mistake.

Hybrid AC/DC Microgrid testing facility for energy management in commercial buildings

With ever increasing energy generation diversity and energy storage becoming affordable, distribution networks are becoming more complex than ever before. This complexity can be utilized to benefit the distribution networks as well as end consumers in the form of controlled Microgrids. Microgrids are not simply distributed generation and energy storage systems; solar systems and battery banks, rather a complete design of hardware and software for specific uses and users. All the different elements need to be designed to work together to provide stable, efficient and sustainable power delivery to the end user. An experimental Hybrid-Microgrid testing facility is presented in this paper that implements high-efficiency distribution architectures combining both AC and DC networks. This testing facility provides a research testbed for investigating different aspects of Microgrid systems, employing a total of 15.5 kW of reconfigurable Solar PV and 80 kWh of lithium energy storage on a 145 kVA commercial building load located at Griffith University. Implementation results along with control system simulation results are presented in this paper for distributed renewable generation, Static Synchronous Compensators, advanced control methodologies and forecasting methods for energy management purposes.

Primary Frequency Response From the Control of LED Lighting Loads in Commercial Buildings

With the increasing contribution of intermittent renewable generations to electric power grids, additional frequency reserves are required to manage the balance between generation and load in power systems. This paper describes the potential contribution of LED lighting loads as frequency reserves to provide ancillary services and proposes a decentralized control strategy for LED lighting loads in response to frequency deviations. Three control modes are developed according to the magnitude and duration of the frequency deviations. Experimental results verify the effectiveness of the use of an illumination controller to regulate illumination with the corresponding control modes. Simulation results demonstrate the validity of using LED lighting loads as frequency reserves to provide frequency regulation. The frequency deviations can be appropriately mitigated using the controlled LED lighting loads.

Objective and subjective evaluation of thermal comfort in the Loccioni Leaf Lab

Thermostatically controlled loads in commercial buildings are usually ruled by set points indicated by well-established international standards like EN 15251. These thresholds set the acceptable comfort ranges based on several parameters such as activity level, climatic conditions and building orientation. However, there are so many aspects which can affect the occupant perception of comfort ranging from physical and mental aspects to cultural aspects while only few of them are clearly measurable.This paper presents a methodology for the simultaneous subjective and objective evaluation of thermal comfort in commercial buildings. The methodology is based on the intermediate protocol level for the evaluation of thermal comfort as suggested by ASHRAE’s Performance Measurement Protocols for Commercial Buildings. It is applied in the office spaces of the Loccioni Leaf Lab, located in the province of Ancona, Italy, during the summer period. The study is utilized for the identification of serious thermal comfort issues but also for the determination of the preferred comfort conditions in the Leaf Lab office spaces.

A Bayesian Network model for predicting cooling load of commercial buildings

Cooling load prediction is indispensable to many building energy saving strategies. In this paper, we proposed a new method for predicting the cooling load of commercial buildings. The proposed approach employs a Bayesian Network model to relate the cooling load to outdoor weather conditions and internal building activities. The proposed method is computationally efficient and implementable for use in real buildings, as it does not involve sophisticated mathematical theories. In this paper, we described the proposed method and demonstrated its use via a case study. In this case study, we considered three candidate models for cooling load prediction and they are the proposed Bayesian Network model, a Support Vector Machine model, and an Artificial Neural Network model. We trained the three models with fourteen different training data datasets, each of which had varying amounts and quality of data that were sampled on-site. The prediction results for a testing week shows that the Bayesian Network model achieves similar accuracy as the Support Vector Machine model but better accuracy than the Artificial Neural Network model. Notable in this comparison is that the training process of the Bayesian Network model is fifty-eight times faster than that of the Artificial Neural Network model. The results also suggest that all three models will have much larger prediction deviations if the testing data points are not covered by the training dataset for the studied case (The maximum absolute deviation of the predictions that are not covered by the training dataset can be up to seven times larger than that of the predictions covered by the training dataset). In addition, we also found the uncertainties in the weather forecast significantly affected the accuracy of the cooling load prediction for the studied case and the Support Vector Machine model was more sensitive to those uncertainties than the other two models.

Integrated automation for optimal demand management in commercial buildings considering occupant comfort

Implementing demand response (DR) in commercial buildings can play a major role in reducing building’s peak load. This improves the efficiency of electricity grids and mitigates expensive peak demand/energy charges for buildings. Due to the lack of Energy Management Systems, small and medium-sized commercial buildings have not historically played much role as a DR resource. This paper presents an integrated control of major loads in commercial buildings, i.e., cooling, lighting and plug loads that can maintain occupant environmental preferences. Each zone’s space temperature set points are optimally adjusted to maintain thermal comfort. Lighting levels, with and without daylight availability, are tightly controlled to maintain desired illuminance levels. Unlike other studies, this research contributes to improvement in functionalities of EnergyPlus by incorporating a 1-min resolution data set at the individual plug load level. The research evaluates total building performance including interdependencies between lighting, plug load, HVAC and control systems interacting in a realistic manner, both among themselves and with building occupants. In this paper, a method to determine the DR potential of a building, i.e., the amount of electrical demand (kW) by load type that can be shifted or shed, is discussed.

Estimating hourly cooling load in commercial buildings using a thermal network model and electricity submetering data

One major obstacle in Heating, Ventilation and Air Conditioning (HVAC) system Fault Detection and Diagnostics (FDD), retrofitting and energy performance evaluation is the lack of detailed hourly cooling load data. Cooling load measurement in commercial buildings is expensive and sometimes very difficult to implement. Detailed building simulation models, such as EnergyPlus, are too complicated to build and also must be calibrated. In this paper, an hourly cooling load prediction model, called the “RC-S” model, is proposed. This new cooling load calculation approach consists of a simplified thermal network model of the building envelope, a thermal network model for the building internal mass and the internal cooling load model from the submetering system. One existing RC model is introduced as reference model and three types of “RC-S” models are set up in this study. Genetic algorithm (GA) is selected to optimize the parameters in those models. Measurement data collected from a real commercial building and simulation data obtained from EnergyPlus model of the same commercial building are used to train and test the four models. The results prove that the proposed “RC-S” cooling load calculation method is more accurate than the existing RC model and much simpler than whole building simulation models. It can provide reasonable estimations of cooling loads for HVAC FDD and other performance evaluations.

Economic analysis of fuel cell installations at commercial buildings including regional pricing and complementary technologies

This paper presents results from sensitivity studies conducted using the Distributed Generation Build-out Economic Assessment Tool (DG-BEAT). The viability of meeting commercial building loads with a stationary fuel cells is studied under different conditions of electricity pricing, dispatch strategies, and complementary technologies. Key findings support the notion that fuel cells are becoming economically viable alternatives in California, New York and Connecticut at installed costs of $7000–10,000/kW. Michigan is identified as another state well suited to fuel cell development with heat recovery. Fuel cell installations reduce net carbon emissions for commercial buildings by 20–30% when compared to local, time-resolved, grid emissions. Grid sell-back, at 50% retail price, significantly improves the economics of a base load fuel cell, but has little impact for a dispatchable system. At installed costs below $5000/kW, load following capability results in significant additional cost reductions as the generating capacity is increased beyond the building's base load requirements. Complementary technologies such as chillers and thermal storage have a pronounced impact, particularly in warmer climates. Installing fuel cells paired with electric chillers and thermal storage in Florida at buildings with exceptionally high air conditioning demands can achieve the same economic benefit as a typical New York building.

Design of Microgrid Energy Supply and Management System with Economic Operation for Charging of Electric Vehicles

This paper presents the design of energy supply and management system to achieve minimum cost of charging the electric vehicles and to reduce the peak power drawn by all electric loads in a microgrid. We consider energy management function at different levels of microgrid like, at stand-alone EV parking lot, at residential loads and at commercial building loads, etc. The energy supply and management system is not only connected to the power grid but also with a combination of fixed Worldwide Interoperability for Microwave Access (WiMAX) and Local Area Network (LAN). First we perform load balancing among different kinds of loads in a microgrid such that extra electrical resource may be transferred to resource constrained loads by using game theoretic approach, and later we propose a distributed algorithm for load scheduling of electric vehicles parked in stand-alone parking lot in microgrid to minimize the sum of total energy cost for charging the battery of electric vehicles and spreading out the charging power equally over the charging time using interior point method (IPM). This results in reduction of peak charging power based on EVs own consumption schedule while they select the best response in energy consumption game.

Future climate change and building energy demand in Tianjin, China

This paper concerns the impacts of future climate change under two forcing scenarios on energy demand of commercial building and residential buildings with different energy-saving levels in Tianjin. Heating load of commercial building will decrease under the two scenarios in the next 90 years but increase of cooling load is found. All residential buildings will decrease heating load in the future 90 years. In particular, the decreasing rate of energy demand during 2011–2100 by the residential building slows down from the first- to the third-stage energy-saving levels. Additionally, the difference in energy demand between the two scenarios becomes smaller as the energy-saving level increases. These suggest that higher energy-saving levels are beneficial for decreasing not only energy consumption but also its sensitivity to climate change. Practical application: Climate change in the future causes the large and significant increase in cooling energy demand but decrease in heating energy demand. This would be helpful for the adjustment of energy use strategy by government. Also, the possible changes in future energy demands for heating and cooling will be of interest to energy providers. The responses of heating energy demand to the future climate change show large difference among the residential buildings with different energy-saving levels. This will provide useful information for policy makers and building industry managers on how to make appropriate measures keep occupants comfort and reduce energy use.

The role of grid-connected, building-integrated photovoltaic generation in commercial building energy and power loads in a warm and sunny climate

For large commercial buildings, power load delivery limits are contracted with the local electricity distribution utility, and are usually fixed at one or more levels over the year, according to the seasonal building loads, and depending on the specific country regulations. Especially in warm and sunny climates, solar electricity generation using building-integrated photovoltaics (BIPV) can assist in reducing commercial building loads, offering peak-shaving (power) benefits on top of the on-site generation of electricity (energy). This on-site power delivery capability gives these consumers the possibility of renegotiating demand contracts with their distribution utility. Commercial buildings that operate during daytime quite often have an energy consumption profile that is well matched by solar radiation availability, and depending on the building’s available surface areas, BIPV can generate considerable portions of the energy requirements. In this work we present the role of grid-connected BIPV in reducing the load demands of a large and urban commercial building located in a warm climate in Brazil. The building and adjacent car parking lots can accommodate a 1 MWp BIPV generator, which closely matches the building’s typical maximum power demands. Based on real solar radiation data and simultaneous building electricity demands for the year 2007, simulation of the annual solar generation profile of this on-site generator showed that the 1 MWp BIPV system could account for around 30% of the total building’s energy consumption. In addition to the energy benefit, maximum power demands were reduced due to a good match between midday air-conditioning cooling loads and solar radiation availability on both a daily and seasonal basis. Furthermore, we have simulated the effect of this considerably large urban-sited generator on the local distribution network load, and have shown that the 1 MWp BIPV installation can also offer considerable benefits to the local utility in shaving daytime peak loads at the corresponding feeder.

Influence of raised floor on zone design cooling load in commercial buildings

The installation of a raised floor system can change the thermal behaviour of the building by reducing the interaction between the heat gains and the thermally massive concrete slab. In this study, the influence of the raised floor on the summer design day zone cooling load profile is evaluated with EnergyPlus for an office building located in San Francisco. The effects of structure type, window-to-wall ratio and the presence of carpet on the thermal behaviour of the raised floor are also investigated. The results show that the mere presence of the raised floor largely affects the zone cooling load profile and the peak cooling load over the range of −7 to +40%. The most significant parameters are the zone orientation, i.e. the exposure to direct solar radiation, and the presence of floor carpeting. If carpeting is present, commonly used in U.S. office buildings, the overall impact on zone peak cooling load is reduced, ranging from 0 to 5% greater for the raised floor than without it. Without carpet the peak cooling load is 4% greater with raised floor than without it in the north zone, 22% in the east and west zones, and 12% in the south zone.

Applications of one-cycle control to improve the interconnection of a solid oxide fuel cell and electric power system with a dynamic load

Adding distributed generation (DG) is a desirable strategy for providing highly efficient and environmentally benign services for electric power, heating, and cooling. The interface between a solid oxide fuel cell (SOFC), typical loads, and the electrical grid is simulated in Matlab/Simulink and analyzed to assess the interactions between DG and the electrical grid. A commercial building load profile is measured during both steady-state and transient conditions. The load data are combined with the following models that are designed to account for physical features: a One-Cycle Control grid-connected inverter, a One-Cycle Control active power filter, an SOFC, and capacitor storage. High penetration of DG without any power filter increases the percentage of undesirable harmonics provided by the grid, but combined use of an inverter and active power filter allows the DG system interconnection to improve the grid tie-line flow by lowering total harmonic distortion and increasing the power factor to unity.

Eficacia de la estreptocinasa en el tratamiento del empiema

Understanding the varying characteristics and aggregate potential of power flexibility from different building types considering regional diversity is critically important to actively engaging building resources in future eco-friendly, low-cost, and sustainable power systems. This paper presents a comprehensive characteristics analysis and potential assessment of the power flexibility from heating, ventilation, and air conditioning loads in commercial buildings in the U.S. using a simulation-based method. Commercial buildings are first grouped by building type and climate region. The U.S. Department of Energy Commercial Prototype Building Models are used to represent an average building in each group and are simulated to characterize power flexibility. Based on building survey data, the number of commercial buildings in each group is estimated and used to calculate aggregate power flexibility. It is found that cooling loads in commercial buildings offer more flexibility for increasing power consumption than for decreasing it. The power consumption of commercial buildings in the U.S. can be increased by 46 GW and decreased by 40 GW on peak summer days. Among all commercial building types, standalone retail buildings provide the most absolute flexibility while medium office buildings have the most flexibility as a percentage of the rated power consumption.