Comparison and analysis of energy consumption of energy-efficient office buildings in different climate regions in China: case studies

Abstract

The purpose of this paper is to analyze the energy consumption (EC) and find out the determining factors of energy-efficient office building cases according to specific case studies in typical cities of different climate zones in China. The investigated building cases were located in four cities (Beijing, Ningbo, Nanjing and Shenzhen) of three architecture thermotechnical design zones (cold zone, hot summer and cold winter zone, hot summer and warm winter zone). The analysis indicates that the energy consumption index (ECI) of these four cases ranges from 41.06 to 74.23 kW·h/(m²·a). Besides, the outdoor climate can change the EC of air conditioning/heating systems, and further determine the monthly volatility of the total EC of the whole building.

Keywords

energy-efficient building / breakdown energy consumption (EC) / energy consumption index (ECI) / different climate zone

Introduction

It is apparent that the lowering of building energy consumption (EC), the vigorous expansion of low EC building and the sustainable development of town construction is the urgent objective of the 21st century in China [1]. The building energy conservation requires that the buildings should adjust to the climate and their function of use. Wan et al. [2] conducted multi-year building energy simulations for generic air-conditioned office buildings in Harbin, Beijing, Shanghai, Kunming and Hong Kong, and observed a decreasing trend of heating load and an increasing trend of cooling load due to the climate change in the future years. Using economic performance as the sole criterion to be optimized, Ren et al. [3] examined the feasible distributed energy resource (DER) systems for three typical building complexes of a major city within each of the five major climate zones in China. Li et al. [4] reviewed the impact of climate change on energy use in buildings in different parts of the world. Using DOE-2, Lam et al. [5] conducted energy simulation for office buildings in five major climate zones in China, and investigated the thermal and energy performance of office buildings with centralized heating, ventilation and air-conditioning plants. Lam et al. [6] investigated the energy performance of office building envelop designs in five major climate zones in China, and analyzed the interactions between lighting and space heating/cooling loads in office buildings of major climate zones, by conducting building energy simulation of DOE-2.1E. Wan et al. [7] studied the availability of excellent solar energy in different climate classifications, using cluster analysis.

The above literature indicates that the building energy conservation requires that the building should adjust to the climatic conditions and its function of use, which is a very important guide to the research of the EC of public buildings in different climatic regions in China.

This paper is based on unitive data descriptive procedure on EC and unitive data model of building subentry EC [8]. It is necessary to choose special building cases in a small range between different climatic regions, by means of building operating EC data acquisition, spot test and statistical analysis. The analysis of the EC of building cases, the control of the air-conditioning system and the service provided by the building can provide references for further suitability study of the low EC building in different climatic zones.

Cases selection and building basic information statistics

Cases selection

Due to its large land area across a wide range of latitudes, the diversities in climates and complexities of topography have led to its distinct climatic features in different regions in China [9]. In terms of the thermal design of buildings in GB50176-93 [10] and GB50365-2005 [11], there are five major climate types, namely, severely cold, cold, hot summer and cold winter, mild, as well as hot summer and warm winter in China. In this paper, according to the distribution feature of climate zones in China, four buildings located in four different cities were considered as case studies for the analysis of the EC of energy-efficient building. The relative locations of the four cities included Beijing, Ningbo, Nanjing, and Shenzhen. These case studies were for two office buildings (B1, N3), a lodging office building (N2), and a green demonstration office building (S4).

Building basic information statistics

Table 1 enumerates the fundamental state of the selected building cases from the point of view of building EC. To expand analysis limits, four building cases from different perspective of architectural scales and application of energy-saving technologies were chosen.

EC statistics

In this paper, the basic EC data were obtained in two ways. The operating records of the gauging devices such as the total meter, sub-meter (heating system, cooling system, domestic hot water system, kitchen fittings, electro-lighting system, office equipments, building service equipments, etc), cold energy meter, hot energy meter assembled in the building were provided by house owners; for the cases having the real-time acquisition and monitoring system, the real-time records were acquired from the data processing center. The statistics of the EC of the four building cases in a year were made in co-ordination with the property sector. In addition, the indoor environments from Nov. 24th to Dec. 7th were measured by personal visits to the houses, and a checking on the energy-consumption data were done according to the spot statistical results of the indoor facilities, and believable data were acquired to make the comparative analyses.

It was found that, besides electricity, other energy sources such as gas and hot water were also used in the four selected buildings. Because electricity is the principal energy, the equivalent electricity methods [12,13] were adopted to transform gas and hot water into equivalent electricity (kW·h), and the total EC was obtained by conversion, in which the reduction coefficient of fuel gas and hot water was 7.131 kW·h/m³ and 0.06435 kW·h/MJ, respectively. The energy consumption index (ECI) results together with those based on GFA are summarized in Table 2. It can be observed from Table 2 that Building N2, the one with the smallest scale, has the most EC per unit. However, since there are many guest rooms, and a lot of people coming and going in N2, it is hard to calculate the per capita annual electric power consumption.

Case studies

The EC feature of the building is reflected by the EC types and the subentry EC split-results of different energy using system [14]. Since the building EC power value will be much different when using different area definition in the computation of the building ECI, the definition of areas is very important for the calculation of energy-consumption target. In this paper, the area definition method of the energy-consumption data description was used to get the statistics of the service areas of different energy using system (Tables 3-6). The total energy-consumption, every sub-energy consumption and energy of different energy using system were analyzed by taking into consideration the climate characteristics of the typical cities in different climatic zones.

A case study of B1 (Beijing)

Table 3 shows that the proportion of the total EC of lighting and office equipment is the largest (62.84%), that of the air conditioning system the second (26.34%), and that of the heating system the third (4.47%). According to the use area of different systems, the per-unit ECI of different systems were acquired, of which, the information equipment room energy using index (434.43 kW·h/(m²·a)) is significantly higher than that of other systems. More electrical equipment and small service areas lead to the higher energy intensity of the information equipment room. To analyze the reasons for the EC differences of different energy using systems, the monthly electrical power consumption was split and the monthly change of the sub-EC with the seasons (Fig. 1) was obtained. The wave motion of the non-air conditioning system/heating system is not apparent with the seasons changing. The error between the peak value and valley value is less than 15%, because the EC of the non-air conditioning system is only linked with the electrical equipment power and its time of use. It can be seen from Table 1 that in the heating season (Jun. 15-Sept. 15), there is a positive correlation between the EC of the air conditioning system and the outside temperature, which is opposite to the cooling season. The electrical power consumption of the air conditioning system has a decisive effect on the total EC of the building.

The EC of the air conditioning system can be further divided into cold site power consumption, air conditioning blower and terminal power consumption, of which, the cold site power consumption includes refrigerator, chilled water pump and cooling tower power consumption. The annual energy consumption (AEC) is 309048.2 kW·h (2010). The split-result is illustrated in Fig. 2. The power consumption of the chiller plant in the air conditioning system accounts for the largest proportion (33%), followed by the water pump and, then the air conditioning terminal. Therefore, to adjust the refrigerator types according to the EC load of the building, the selection of a reasonable water-cooled screw chiller (LAWSM) is very crucial for reducing the EC of the air conditioning and the EC of the whole building.

A case study of N2 (Ningbo)

Table 4 lists the split-result of the ECs of different buildings. The EC of cooling/heating is an important component of the EC of the whole building, which determines the change of the total EC. The energy density of kitchen fittings is the highest [123.33 kW·h/(m²·a)], because of the many high EC equipment and small service areas in the kitchen.

In Table 4, the EC of cooling and heating presents regularity with the outdoor temperature change (the EC of air conditioning is directly proportional to the outdoor temperature, the EC of heating is inversely proportional to the temperature), which has a decisive influence on the wave motion of the EC of the building. The domestic hot water energy in the heating season is three times more than that in the summer, which is determined by the type (function) of the building (lodging and official). The wave motions of the EC of the blower and cooking equipment are not large, and the error between the peak and valley value is less than 10%, which can be almost ignored. The wave motions of the EC of other non-air conditioning systems are obvious, because those wave motions result from human activity, and there is no obvious discipline in EC changes. So the operation of the building managers, the adjustment and participation of building users are important factors influencing the EC of the building.

A case study of N3 (Nanjing)

It is observed from Table 2 that the monthly average electricity consumption of N3 is 72748.67 kW·h. And taking Fig. 3 into consideration, it is not difficult to find out the changes of the monthly total EC of this building. In Dec., Jan., July and Aug., the EC is higher than average. The main reason for this is that in those months, N3 needs to supply heating and cooling so that the EC of the HVAC system may be higher, which directly leads to the increase in the total EC of the building. Table 5 demonstrates the result of the breakdown EC of each item in Case N3. It is noticed from Table 5 that the EC of cooling/heating accounts for 47% of the total, which is the largest share. In addition, the EC for cooling in summer is higher than that for heating in winter.

For N3, the outdoor temperature in July reaches up to 27.9°C, which is already the highest monthly average temperature in the whole country. Meanwhile, the EC also arrives at the highest, which is 1159999 kW·h for this building. The EC of cooling accounts for approximately 61% of the total. In Jan. the outdoor average temperature is 2.1°C, and the EC in this month also approaches to 93258 kW·h, which also exceeds the average. The EC of heating amounts to approximately 61.1%. For the mild months such as Mar., Apr., Oct. and Nov., the whole monthly EC also reduces a lot. The outdoor temperature influences the cooling and heating load to change the amount of EC of the HVAC and further decides the EC of the building.

A case study of S4 (Shenzhen)

As the main energy source, the electricity for S4 is supplied by the city electricity grid and the green electricity from the building solar photovoltaic power generation system. The photovoltaic power generation system parallels with the city electricity grid and supplies the electricity power together, in the way of “parallel grid.” The electricity consumption from the power grid is 1025863.05 kW·h, accounting for 93.98%, while the green electricity consumption is 65750 kW·h, amounting to approximately 6.02%. According to computation, Table 6 displays the summary of breakdown EC for S4, in which the air conditioning system shares 33% of the total EC, followed by office equipment (24%), and the information system room (17%).

S4 is located in the hot summer and warm winter area. Figure 4 indicates that there is no EC for heating but air conditioning EC exists throughout the whole year. In the highly hot and humid outdoor environment, the cooling load increases dramatically, which causes a high air conditioning consumption. The outdoor climate is mild in other seasons so that the cold machine of the air conditioning does not need to run. The air conditioning is just used for ventilation, and the EC is low. Therefore, the outdoor climate condition significantly influences the EC of the building, and the monthly average EC in the non-cooling season only accounts for 43.43% of that in summer.

Discussion and conclusions

The EC of four energy-efficient building cases in Beijing, Ningbo, Nanjing, and Shenzhen was studied. These cities are located in three major climate zones, namely the cold, the hot summer and cold winter, and the hot summer and warm winter zone in China. The EC data of the building were obtained based on the operation of log or energy monitoring system.

1) Electricity is the main energy source in these four cases. However, municipal hot water and gas are also used in B1 and N2 to meet the demands of heating and cooking. The power consumption indicators of the four cases range from 41.06 to 71.35 kW·h/(m²·a), and the total EC indicators corrected by the equivalent electrical method is between 41.06 kW·h/(m²·a) and 74.23 kW·h/(m²·a).

2) Comparing the breakdown EC of different items within the four building cases, it can be noticed that, besides the EC used for lighting and indoor office equipment, the EC for cooling and heating accounts for the largest proportion of the total EC. For this reason, the total EC is influenced markedly by the heating/ cooling EC inside the building. On account of the cold/ heat load of the building, the outdoor climate can change the EC of the air conditioning/heating systems, and further influence the total EC of the whole building.

3) The electric consumption of illumination and office equipment is also very high. However, the variation range of illumination and office equipment is much smaller than that of the heating and cooling system. The amount of EC for the non-air conditioning system just depends on the power and the service time of the equipment.

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