A Novel Control Strategy for Improving the Performance of a Nearly Zero Energy Building

Tsioumas, Evangelos; Jabbour, Nikolaos; Koseoglou, Markos; Mademlis, Christos

doi:10.1109/tpel.2019.2921107

Cited by 14 publications

(5 citation statements)

References 37 publications

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“…Han-Ding G has constructed an implementation path for developing the ES renovation market of existing buildings from three dimensions: practical concepts, practical processes, and practical methods [8]. Tsioumas E discussed the most challenging energy management issues in near zero energy buildings [9]. Gao G believed that it is crucial to design ES building thermal comfort control strategies that can reduce the EC of HVAC while maintaining the comfort of residents [10].…”

Section: Related Workmentioning

confidence: 99%

Simulation on Energy-Saving Control of Building Operation on Basis of Adaptive Fuzzy Algorithm

Yanqiu

2024

J. Phys.: Conf. Ser.

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Currently, residential construction in China is in a stage of rapid growth, and building energy consumption (EC) is a very significant issue. Among them, the EC of building air conditioning accounts for a large proportion, so how to improve the efficiency of building use is the key to improving building EC. This article intended to use EnergyPlus software to numerically simulate residential EC in different types, numbers of people, weather conditions, and other environments. The simulation results can be analyzed and processed to determine the optimal building operating parameters. This article intended to explore from two aspects: the architectural elements in independent spaces and the overall structure. The control group is a traditional building energy-saving (ES) control method, and the experimental group is a control method based on an adaptive fuzzy algorithm (AFA). The EC and comfort evaluation values of the two groups under the same working conditions are compared and analyzed. The EC of the traditional building ES control method is 120kWh/m2/year, and the EC of the control method based on the AFA is 95kWh/m2/year. The ES control simulation of building operation based on AFA has a reference effect on the adjustment of building EC.

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Section: Related Workmentioning

confidence: 99%

Simulation on Energy-Saving Control of Building Operation on Basis of Adaptive Fuzzy Algorithm

Yanqiu

2024

J. Phys.: Conf. Ser.

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“…The basic form of GM (1,1) can be obtained by combining Formula (1)-( 5), as shown in (6). The differential equation model (albino differential equation) is shown in (7) [36]. In the following part, we can use Equation ( 6) to solve the parameter a b, and then use (7) to solve the predicted value.…”

Section:  mentioning

confidence: 99%

“…To improve the energy structure of countries and deeply reduce carbon dioxide emissions [2], it has become the consensus of researchers in the power domain to absorb widely distributed renewable resources through distributed power generation equipment [3], [4]. As an important carrier of renewable energy production and use, the energy storage system (ESS) can realize the time-space shift of renewable energy [5], stabilize the fluctuation of load, reduce the cost of electricity [6], and improve the local consumption capacity of renewable energy [7]. However, ESS has the characteristics of high investment cost and long return period, resulting in low enthusiasm of investors and only taking a wait-and-see attitude.…”

Section: Introductionmentioning

confidence: 99%

Study of Long-Term Energy Storage System Capacity Configuration Based on Improved Grey Forecasting Model

Feng

Zhang³

et al. 2023

IEEE Access

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Distributed generation equipment improves renewable energy utilization and economic benefits through an energy storage system (ESS). However, dominated by short-term data, the configuration of long-period ESS capacity is absent based on the dynamic change of load, which leads to a large deviation from the expected return. Considering the system characteristics of lack of data and less information, after introducing the grey theory, we propose a new long-term capacity configuration method for ESS and establish the long-term grey forecasting model (GFM) of user load, improving the basic forecasting model to improve the accuracy of the long-term forecasting model. Then, the scheduling model is established with the maximum economic and social benefits as the optimization objective. Based on the forecast data of the improved grey forecasting model (IGFM), the hierarchical solution method is used to solve the scheduling model. Finally, the parameters are configured based on the service life of the equipment and the expected rate of return. The simulation results show that higher accuracy is realized in the improved prediction model, and the improved algorithm gets higher convergence speed and precision. Apart from that, the nonlinear correlation trend of the EES return rate between the capacity and life cycle is revealed. Compared with the ESS configuration in a short period, this study provides more comprehensive and accurate data support for the capacity configuration of the ESS, reducing the error between the actual return and the expected return significantly.

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“…Therefore, researchers are seeking measures that can increase the energy efficiency and decrease the energy demand of buildings. Zero energy buildings (ZEB) have been widely studied because of their advantage in energy-saving and environmental protection and have been regarded as a promising solution [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Retrofitting Strategies Based on Orthogonal Array Testing to Develop Nearly Zero Energy Buildings

Wang

Zhang

2022

Sustainability

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Retrofitting existing buildings to be a nearly zero energy building (nZEB) is an effective solution for greenhouse gas emissions and primary energy consumption reduction. A hybrid approach that integrates the building energy simulation method and orthogonal array testing (OAT) to renovate buildings to nZEB is proposed in this paper. Within a residential building in Changchun, Jilin of China, the total energy consumption index (TECI) and CO2 emission factor for heating are used as evaluation criteria. The reliability of the building energy model is validated and adopted to forecast the energy performance of different building renovation strategies. According to OAT, four passive measures can be ranked by their influence on TECI in descending order as follows: external wall heat transfer coefficient, airtightness, window heat transfer coefficient, and roof heat transfer coefficient. The optimal renovation solution of the studied building can reduce the TECI by 43.18% by only reducing the external wall heat transfer coefficient from 0.5 to 0.2 W/m2·K and the infiltration N50 from 3.6 to 0.4 ac/h. Besides, combined heat and power (CHP) utilities emit less CO2 than heat pumps in providing heating under the current CO2 emission factor of the power grid in China, making it impossible to give up district heating systems until carbon emissions of electricity generation have declined significantly. The results can provide a reference for the application of the nZEB standard in actual retrofitting projects.

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A Novel Control Strategy for Improving the Performance of a Nearly Zero Energy Building

Cited by 14 publications

References 37 publications

Simulation on Energy-Saving Control of Building Operation on Basis of Adaptive Fuzzy Algorithm

Simulation on Energy-Saving Control of Building Operation on Basis of Adaptive Fuzzy Algorithm

Study of Long-Term Energy Storage System Capacity Configuration Based on Improved Grey Forecasting Model

Retrofitting Strategies Based on Orthogonal Array Testing to Develop Nearly Zero Energy Buildings

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