Benchmarking cooling and heating energy demands considering climate change, population growth and cooling device uptake

Mutschler, Robin; Rüdisüli, Martin; Heer, Philipp; Eggimann, Sven

doi:10.1016/j.apenergy.2021.116636

Cited by 72 publications

(25 citation statements)

References 29 publications

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“…In addition to the proposed optimal‐BRA based ANN for LF, the concept of degree days is also a tool to analyse weather‐related energy consumption for heating and cooling appliances in buildings. It is helpful to predict buildings' energy consumption and gaseous emissions 64‐66 . Degree‐days are characterized as the aggregate of the temperature differences between the outdoor temperature and a base temperature.…”

Section: Estimation Of Acs Demand Based On Cdds and Hddsmentioning

confidence: 99%

“…It is helpful to predict buildings' energy consumption and gaseous emissions. [64][65][66] Degree-days are characterized as the aggregate of the temperature differences between the outdoor temperature and a base temperature. The outdoor temperature at which there is no requirement to operate cooling or heating appliances for end-user's comfort attainment is taken as reference, base, or balance point temperature.…”

Section: Estimation Of Acs Demand Based On Cdds and Hddsmentioning

confidence: 99%

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Optimal BRA based electric demand prediction strategy considering instance‐based learning of the forecast factors

Waseem

Liu

Zhang

et al. 2021

Int Trans Electr Energ Syst

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With the grid's evolution, the end-users demand becomes more vital for demand side management (DSM). Accurate load forecasting (LF) is critical for power system planning and using advanced demand response (DR) strategies.To design efficient and precise LF, information about various factors that influence end-users demand is required. In this paper, the impact of different factors on electrical demand and capacity of climatic factors existence and their variation is discussed and analysed. The Pearson correlation coefficient (PCC) is utilized to express the degree of electric demand correlation with metrological and calendar factors. Then, the optimal-Bayesian regularization algorithm (BRA) based on ANN for LF is presented. The effect of the number of neurons in hidden layers on output is observed to select the most appropriate option. Additionally, heating degree days (HDDs) and cooling degree days (CDDs) indices are investigated to consider the impact of air conditioners' (ACs) loads in different seasons. Case studies on data from Dallas, Texas, USA, are used to

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Section: Estimation Of Acs Demand Based On Cdds and Hddsmentioning

confidence: 99%

Section: Estimation Of Acs Demand Based On Cdds and Hddsmentioning

confidence: 99%

Optimal BRA based electric demand prediction strategy considering instance‐based learning of the forecast factors

Waseem

Liu

Zhang

et al. 2021

Int Trans Electr Energ Syst

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“…Several literature values are pertinent for this research concerning the existing Kazakhstani buildings and thermal demand. The average heating energy consumption for residential buildings in Switzerland was reported to be 101 kWh/m 2 in 2018 [48]. According to [49], the annual energy use performances across three Canadian cities, such as Quebec, Toronto, and Vancouver, are 126.08 kWh/m 2 , 116.47 kWh/m 2 , and 98.47 kWh/m 2 for the period from 1998 to 2014, respectively, and 126.03 kWh/m 2 , 115.31 kWh/m 2 , and 100.25 kWh/m 2 , respectively, according to forecasting future climate conditions.…”

Section: The Optimum Heating and Cooling Loads Reduction For Entire T...mentioning

confidence: 99%

An Exhaustive Search Energy Optimization Method for Residential Building Envelope in Different Climatic Zones of Kazakhstan

et al. 2021

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Nowadays, the residential sector of Kazakhstan accounts for about 30% of the total energy consumption. Therefore, it is essential to analyze the energy estimation model for residential buildings in Kazakhstan so as to reduce energy consumption. This research is aimed to develop the Overall Thermal Transfer Value (OTTV) based Building Energy Simulation Model (BESM) for the reduction of energy consumption through the envelope of residential buildings in seven cities of Kazakhstan. A brute force optimization method was adopted to obtain the optimal envelope configuration varying window-to-wall ratio (WWR), the angle of a pitched roof, the depth of the overhang shading system, the thermal conductivity, and the thicknesses of wall composition materials. In addition, orientation-related analyses of the optimized cases were conducted. Finally, the economic evaluation of the base and optimized cases were presented. The results showed that an average energy reduction for heating was 6156.8 kWh, while for cooling it was almost 1912.17 kWh. The heating and cooling energy savings were 16.59% and 16.69%, respectively. The frontage of the building model directed towards the south in the cold season and north in the hot season demonstrated around 21% and 32% of energy reduction, respectively. The energy cost savings varied between 9657 to 119,221 ₸ for heating, 9622 to 36,088 ₸ for cooling.

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“…As the temperatures increase, cooling energy consumption also increases gradually [16]. Urban heat island leads to a 19% median increase in cooling energy consumption [17].…”

Section: Introductionmentioning

confidence: 99%

The Use of Horizontal Shading Devices to Alleviate Overheating in Residential Buildings in the Severe Cold Region and Cold Region of China

Chang

et al. 2022

Buildings

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Global warming is resulting in higher summer indoor temperatures in the severe cold region and cold region of China, and this is affecting thermal comfort. Local building design codes consider these regions as cool in summer, and do not consider the phenomenon of overheating or propose countermeasures. This paper studied the possibility of overheating in residential buildings in these areas. It suggested alleviating this phenomenon using external horizontal shading, and discussed how to integrate thermal comfort into the building design and save energy consumption. The IESVE software was used to simulate 18-storey residential buildings with natural ventilation in Yichun, Harbin, Shenyang, Dalian, and Beijing, and to calculate the change in indoor operative temperature. Horizontal shading was designed for case study building to attempt to alleviate the overheating phenomenon in summer. The results showed that the case study building in the five cities experienced different degrees of overheating. External horizontal shading was successful in reducing indoor overheating, especially in the severe cold B and C zones and the cold A and B zones. The relevant building codes should be modified to take this into account. Reasonable design of horizontal shading can effectively reduce energy consumption, particularly when compared with air-conditioned buildings.

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Benchmarking cooling and heating energy demands considering climate change, population growth and cooling device uptake

Cited by 72 publications

References 29 publications

Optimal BRA based electric demand prediction strategy considering instance‐based learning of the forecast factors

Optimal BRA based electric demand prediction strategy considering instance‐based learning of the forecast factors

An Exhaustive Search Energy Optimization Method for Residential Building Envelope in Different Climatic Zones of Kazakhstan

The Use of Horizontal Shading Devices to Alleviate Overheating in Residential Buildings in the Severe Cold Region and Cold Region of China

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