Evaluation Of Energy Saving Potential Research Articles

Energy-saving potential benchmarking method of office buildings based on probabilistic forecast

Building energy consumption represents a substantial portion of China's total energy usage profile. Conducting a quantitative assessment of the energy-saving potential in buildings is crucial, as it aids in estimating the investment risk and payback period for energy-efficient projects. This evaluation also informs the development and formulation of policies promoting building retrofits and energy conservation. However, this field's present state of research exhibits a significant gap. This study takes 8 typical office buildings as case objects and conducts relevant research on quantitative evaluation of energy-saving potential. On the basis of quantile regression, three corresponding probabilistic forecasting models for building energy consumption are established by combining the classic time series prediction algorithm Long Short-Term Memory (LSTM) in data-driven methods, Gradient Boosting Decision Tree (GBDT) in known building energy benchmarking, and a relatively simple linear model. The evaluation results demonstrate that the LSTM-QR model can serve effectively as a probabilistic forecasting model for estimating building energy-saving potential. Based on the LSTM-QR model results, a quantitative evaluation method for building energy-saving potential benchmarking is proposed, utilizing linearized Cumulative Distribution Function (CDF) curves. This method can quantitatively assess the energy-saving potential of the studied buildings. By analyzing and comparing these buildings' hourly energy consumption data over the past three years, it is evident that the quantitative scoring results from this method can provide directional guidance for building renovation projects to enhance energy efficiency.

Towards China's dual-carbon target: Energy efficiency analysis of cities in the Yellow River Basin based on a “geography and high-quality development” heterogeneity framework

The Yellow River Basin (YRB) serves as a critical energy hub in China. Enhancing energy efficiency in cities across the YRB is pivotal for achieving high-quality development and meeting carbon peaking and neutrality targets. This paper proposes a multidimensional technology heterogeneity assessment framework to refine the classification of production technologies. It leverages this framework to develop a data envelopment analysis model for evaluating green total factor energy efficiency (GTFEE) in 78 cities within the YRB from 2006 to 2022. The key findings are as follows: (1) Grouping outcomes from the multidimensional heterogeneity framework significantly differ from existing literature. (2) GTFEE shows notable spatiotemporal variations within the YRB, with a substantial overall increase since 2011. However, cities in the central YRB exhibit lower GTFEE performance. (3) Energy inefficiency in groups 1, 2, and 3 is attributed to developmental inefficiency, management inefficiency, and practical inefficiency, respectively. (4) Evaluation of energy-saving potential reveals an average annual potential of around 8 million tce per city during 2006–2022. The study concludes with strategies for enhancing GTFEE based on dynamic GTFEE decomposition outcomes, supporting policy design for achieving dual-carbon goals through improved energy efficiency in the YRB region.

Evaluation of energy-saving potential and indoor thermal environment of passive solar houses in various heating climate regions of China

ABSTRACT Passive solar houses comprise crucial strategies of reducing heating and cooling energy for buildings, which have been extensively used in plenty of nations. This study develops a study on indoor thermal environment, the energy-saving performance and natural lighting in different heating climate regions (represented by Lhasa, Xining and Urumqi). An attached-sunspace solar house integrated with phase change material floors is also proposed to ameliorate indoor thermal comfort and simultaneously diminish the heating energy consumption. In addition, the dominant factors analysis of building envelope affecting building energy consumption are sensitively studied. Moreover, the influence of the depth of sunspace and the intensities of internal heat gain on indoor thermal conditions and heating energy consumption are further analyzed. The results indicate that among the three types of solar houses, the passive solar sunspace offers the most stable indoor temperature and Trombe-wall solar houses and attached-sunspace solar houses have striking energy-saving advantages compared with the traditional houses. And the annual power consumption of 695.1 kWh, 427.4 kWh and 688.8 kWh in Lhasa, Xining and Urumqi can be saved in view of natural lighting respectively. Additionally, the whole natural temperature of attached-sunspace solar house is on the rise apparently when the PCM floors are embedded in the house and the energy saving fraction of these three regions is 81.9% for Lhasa, 68.8% for Xining, 55.7% for Urumqi respectively with the integration of phase change floors. The sensitivity analysis of key parameters impacting building energy consumption from high to low are the heat transfer coefficient of external wall, the ratio of window to wall, air tightness, the heat transfer coefficient of external window, and the heat transfer coefficient of roof. The depth of 1.2 m for sunspace is recommended as the optimal choice. Indoor natural temperature is on the rise as intensities of internal heat gain increase. The same downward trend for the main bedroom and the whole building is displayed with the increasing interior heat sources in terms of annual heating load.

Evaluation of energy-saving potential and cabin thermal comfort for automobile CO2 heat pump

Currently, the heat pump air conditioning system is extensively used in Electric Vehicle (EV). However, most previous simulation studies focused on one-dimensional (1D) system performance rather than three-dimensional (3D) cabin thermal comfort. This study proposed a novel control strategy for the operation of a one- and three-dimensional coupling transcritical CO2 heat pump air conditioning system based on the weighted Predicted Mean Vote (PMV) model. The mathematical characterizations of the multiple thermodynamic systems were achieved by one-dimensional calculation and the cabin thermal environment was described by three-dimensional simulation. The weighted predicted mean vote value was calculated by real-time interactive three-dimensional cabin thermal environment parameters while providing control signals for the one-dimensional refrigeration system. The simulation comparison revealed the influence of the weighted Predicted Mean Vote control strategy on the system’s thermodynamic parameters and energy-saving potential. Results showed that the compressor power consumption of the Predicted Mean Vote control strategy was reduced by 9.1%-33.7%, compared with the method of presetting specific temperatures. The proposed one- and three-dimensional coupling method of cabin thermal management establishes the structured correlation between heat pump air conditioning system and cabin thermal environment. The weighted Predicted Mean Vote control strategy reduces the system power consumption within the thermal comfort range of the passengers, and it provides a novel idea for cabin thermal management during practical engineering.

User-side energy-saving potential assessment method based on non-intrusive load identification technology

With the development of smart grid, smart meters have been widely used, and the Non-Intrusive Load Monitoring (NILM) technology for sensing and identifying electricity load has gradually matured. Aiming at the problem that the characteristics of industrial users’ load status are few and the gap between different industries is large, this paper uses the random forest algorithm to build a load identification model, and at the same time builds an energy-saving potential evaluation index system including three dimensions of economy, technology and management. Based on the load identification results, users can evaluate the energy-saving potential, and output the use strategies and power consumption suggestions of electric equipment.

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. Ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

Assessment method of comprehensive energy saving potential of distribution network considering source-load power uncertainty

Abstract The comprehensive energy-saving potential evaluation method of the energy-saving schemes of a distribution network considering the power uncertainty of source and load is studied in this paper. The K-means clustering method is firstly employed to extract typical scenarios of distribution network, and the forward-push back method is used to calculate the power flow in typical scenarios, then energy-saving reconstruction schemes are formulated according to the power flow calculation results. A comprehensive energy saving potential evaluation index system that consists the improvement rate of network loss, line loss rate, transformer loss rate, annual electricity saving cost, annual equipment investment cost, annual maintenance cost and voltage quality improvement rate is built, and the comprehensive evaluation method based on DEMATEL-ANP-TOPSIS mixed decision model is used to evaluate the comprehensive energy-saving potential of the energy-saving reconstruction schemes regarding the index system. Finally, the optimal reconstruction scheme is selected based on the evaluation results of energy saving potential in multiple scenarios. The effectiveness of the proposed method is verified by an example in IEEE-33 node distribution network.

Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings

In some fields, such as the semiconductor manufacturing process, museum, pharmaceutical, and medicine manufacturing industry, the HVAC system needs a very fast response time to protect products and more energy-efficient buildings than traditional controllers. So, the proposed controller is designed to overcome such problems by using integrated fuzzy PI-PD Mamdani-type (FPIPDM) and cluster adaptive training based on Takagi-Sugeno-Kang (CABTSK) type. The spans of the fuzzy membership functions of the FPIPDM are tuned online by the Nelder-Mead simplex search (NMSS) algorithm to minimize time response, while the CABTSK model is tuned offline and online using a gradient descent (GD) algorithm to enhance the stability of the overall system and reject disturbances. Then, the integration framework is used to enable the concept of time-optimal based on the bang-bang code delegation. In this sense, a selected switch delegates the execution of proper control code to the action processor that provides computational resources to control indoor conditions. The predicted mean vote (PMV) index provides a higher comfort level than the temperature, as it considers six variables related to thermal comfort. The results of the proposed structure show that it improves the overall output accuracy and significantly reduces the response time. Furthermore, it increases the robustness of the indoor conditions and it is quite applicable to the MIMO HVAC systems processes with strong coupling actions between temperature and humidity, large time delay, noise, disturbances, nonlinearities, and imprecise identification model.

Performance analysis for a new hybrid air conditioning system in hot-humid climates by simulation

Abstract Energy recovery, evaporative cooling and multiple evaporator are regarded as the effective and energy-efficient techniques to improve the energy efficiency of air conditioning system and reduce building energy consumption. In this paper, a parametric analysis and energy-saving potential evaluation for a new hybrid air conditioning system (HAC) under hot-humid climates are carried out theoretically based on detailed models. The proposed HAC incorporates into a dual-evaporator air conditioning system with an independent fresh air conditioner for both total and sensible energy recovery. One evaporator is installed between the total and sensible energy recovery loop of the fresh air conditioner to deeply dehumidify the fresh air for indoor humidity control. The other evaporator is installed inside the conditioned room to handle the indoor return air for temperature and humidity independent control. The parametric analysis mainly for the effect of air-to-water heat capacity ratio, ambient temperature, enthalpy-humidity ratio of the air-conditioned room and the number of heat/mass transfer units of the internal heat exchangers. The energy-saving potential of the HAC is also evaluated for applications in four typical cities (Changsha, Guangzhou, Fuzhou and Hangzhou) located in southern China over the summer period (June–August). The results show that, for the same air supply requirement, the HAC has an average energy-saving rate of 48.87% compared to conventional system with electric heater, and its power saving per hour is 24.85 W m−2.

Theoretical performance analysis of a new hybrid air conditioning system with two-stage energy recovery in cold winter

Abstract Energy recovery technologies can effectively improve the energy efficiency of air-conditioning systems and significantly reduce building energy consumption. In this paper, a parametric analysis and energy-saving potential evaluation for a new hybrid air conditioning system (HAC) is carried out theoretically based on developed models. The proposed HAC incorporates into a conventional mechanical vapor compression air conditioning system with an independent fresh air conditioner which is composed of a network of heat exchangers, including a packed bed and three air-water finned coils. Under cold winter climate, in the fresh air conditioner, a packed bed is coupled with a water-air heat exchange coil to form a total energy recovery loop. A run-around sensible energy recovery loop is also integrated in the system to produce a two-stage energy recovery effect. Moreover, a sprayer is installed upstream of the two-stage energy recovery process for fresh air humidification, and a fresh air recirculation duct is equipped for frost-free operation. In the parametric analysis, four independent affecting parameters are included: the air-to-water heat capacity ratio, the indoor temperature, the ambient temperature, and the ratio of recirculation fresh air. The energy-saving potential of the HAC is also evaluated for applications in seven typical cities located in middle-lower Yangtze River region of China over the winter period (December, January and February). The results show that compared with the conventional system with electric humidification, the HAC has an average energy saving rate of 44.0%, and its average power saving per hour is 13.41 W m−2.

Theoretical performance analysis of a new hybrid air conditioning system in hot-dry climate

Abstract A parametric analysis and energy-saving potential evaluation for a new hybrid air conditioning system (HAC) under hot-dry climate are carried out theoretically based on developed models. The HAC incorporates into a conventional air conditioning system with an independent fresh air conditioner which is actually composed of a network of heat exchangers, including a packed bed and three air-to-water cooling coils. The fresh air conditioner can switch its work mode by changing the network connecting relations so as to adapt to different climate conditions. Under hot-dry climate conditions, the network can work like an external dew-point evaporative cooler (DPEC) using the exhaust air as the working gas, which is precooled in one of the three cooling coils. The other two coils are used for fresh air cooling and can be arranged in either parallel mode (HAC-P) or series mode (HAC-S). A sprayer is also designed for appropriate fresh air humidification before DPEC process. For parametric analysis, five independent affecting parameters are included: the air-to-water heat capacity ratio, the ambient temperature and humidity, the characteristic number of heat transfer units of the internal heat exchangers, and the fresh air flowrate. In this article, the energy-saving potential in the HAC-P mode is evaluated for applications in five northwest China cities—Karamay, Urumqi, Hami, Jiuquan and Lanzhou over the summer period (from June to August). The results show that the energy-saving rates are between 42.5% and 64.0% when it is compared with the conventional system.

Evaluation of Energy Saving Potential for Small and Medium Enterprises (SMEs) in Thailand

Thailand focused on the energy conservation in designated factories and commercial buildings for more than 25 years, by the promulgation of the Energy Conservation Promotion Act, B.E.1992. However, there are many enterprises (i.e. factories and commercial buildings) which are not in the regulation’s target but consume high amount of energy. This study focuses on the potential energy saving from the so called SMEs (in energy pattern) in Thailand. By using on-site energy consumption and production survey to the 860 SMEs covering eight industry and six commercial building sub-sectors over the country and energy savings by using ODEX estimation, we found that the estimated energy conservation potential in factories and commercial buildings are 881.43 GJ and 442.94 GJ, respectively. Food and beverage, especially in food canning has highest energy reduction potential in industry while hotel and hospital has highest potential saving in commercial building. The obstacles of the energy efficiency improvement in SMEs are also discussed.

Simulation Based Evaluation of Energy Saving Potentials in the Field of Electric Drives Manufacturing

As the production of green products progressively influences customers’ purchase decisions, the development, assessment and controlling of energy sparing processes increasingly has to be focused. Here, one major industry sector that has to be considered is the field of electric drives manufacturing, as the main amount of industrial used energy is consumed in electric engines. Consequently, main research activities in this field focus on the development of stable processes guaranteeing high efficiency levels of the produced motors. However, aside from the products’ energy efficiency, also the energy consumptions of the actual manufacturing steps have to be improved. For this purpose, the present paper presents the main energy consumers within the assembly line of an industrial induction engine. It also explains main energy reduction measures, which were evaluated using a combined material and energy flow simulation. Hereby, the line’s base load as well as the peak load was reduced.

Design and Develop Resources Investigation and Evaluation System of Electric Power DSM

More and more deep integrated resource planning methods and demand side management (DSM) technologies have been studied and applied in China. Using technological and economic means of DSM, exploiting energy-saving potentialities from demand side, balancing load, easing contradictions of power structure, improving energy utilization rate, etc. have been important tasks in electric power enterprises. Based on this background, the paper designed and developed resources investigation and evaluation system of electric power DSM, which could investigate electricity resources of DSM of China, and implement energy-saving potential evaluation and energy efficiency analysis. From aspects of technology, economy, management, etc. suggestions were proposed for DSM, trying to be more rational and effective to allocate and use electricity resources, seeking satisfaction of power demands to the greatest degree, thus promote sustainable development of electric power enterprises effectively.

Evaluation of Energy Saving Potential for the Commercial Sector at the City Scale considering Updating of the Existing Building Stock

Evaluation of Energy Saving Potential for the Commercial Sector at the City Scale considering Updating of the Existing Building Stock

Evaluation of Energy Saving Potential for the Commercial Sector at the City Scale considering Updating of the Existing Building Stock

Evaluation of Energy Saving Potential for the Commercial Sector at the City Scale considering Updating of the Existing Building Stock