ScienceDirect Energy Procedia 00 (2017) 000–000 ScienceDirect Available onlineatatwww.sciencedirect.com www.sciencedirect.com Available online Available online at www.sciencedirect.com ScienceDirect ScienceDirect www.elsevier.com/locate/procedia Energy Procedia 00 (2017) 000–000 www.elsevier.com/locate/procedia Energy (2017) 000–000 631–636 EnergyProcedia Procedia122 00 (2017) www.elsevier.com/locate/procedia CISBAT 2017 International Conference – Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale, CISBAT 2017 6-8 September 2017, Lausanne, Switzerland CISBAT 2017 International Conference – Future Buildings & Districts – Energy Efficiency from Integration Renewable Energy in 6-8 theSeptember Built Environment (Electricity, Nano toofUrban Scale, CISBAT 2017 2017, Lausanne, Switzerland 15th International Symposium on District Heating andfor Cooling Using air The source heat pump air heater(ASHP-AH) rural space Heating and Cooling) heating and power peakthe load shifting Using air source pump air for rural space Assessing theheat feasibility of heater(ASHP-AH) using heat demand-outdoor heating Hui andLe, load temperature function for apower long-term heat demand forecast Haoyuepeak Li,Yidistrict Jiang*shifting Building Energy Research Center,Beijing,10084,China * a b Le, Haoyue Li,Yi Jiang I. Andrića,b,c*, A. Pinaa,Hui P. Ferrão , J. Fournier ., B. Lacarrièrec, O. Le Correc Energy Research Center,Beijing,10084,China IN+ Center for Innovation, TechnologyBuilding and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract a In order to mitigate the severe atmospheric pollution caused by the gas emission of scattered coal consumption during winter in Abstract the Beijing-Tianjin-Tangshan area, a winter space heating scheme based on the use of an air source heat pump is proposed. This Abstract scheme clean the heating rural areas by enhancing theby efficiency of electric adjustment through peak shifting. In order offers to mitigate severeinatmospheric pollution caused the gas emission of peak scattered coal consumption during winterThe in paper firstly introduces how toarea, use air sourcespace heat pumps toscheme replacebased heating stoves forofrural residential heating, then explains This how the Beijing-Tianjin-Tangshan a winter heating on the use is proposed. an air source heat pump District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the to use this heating method to in adjust power load. Finally, computation and verification was carriedThe out scheme offers clean heating areaspeak bysector. enhancing efficiency ofanalysis electric peakexperimental adjustment through peak shifting. greenhouse gas emissions fromrural the building Thesethe systems require high investments which are returned through the heat to show the effects on the power grid in the Beijing-Tianjin-Hebei area and on farmer households if all the 6 million farmer paper how toclimate use air source heat and pumps to replace heating stoves for heat rural demand residential thencould explains how sales.firstly Due introduces to the changed conditions building renovation policies, in heating, the future decrease, households in the Beijing-Tianjin-Hebei Region were Finally, to use this heating method. to use this heating method toreturn adjustperiod. power peak load. computation analysis and experimental verification was carried out prolonging the investment © 2017 The Authors. by Elsevier Ltd. to show thescope effects onPublished the power in the the Beijing-Tianjin-Hebei area demand and on –farmer households if all the 6 for million The main of this paper is togrid assess feasibility of using the heat outdoor temperature function heat farmer demand Peer-reviewinunder responsibility of the scientific committee of the scientific committee of the CISBAT 2017 International households the Beijing-Tianjin-Hebei Region were to use this heating method. forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Conference –Authors. Future Buildings &byDistricts Energy Efficiency from Nano to Urban Scale. ©buildings 2017 Thethat Published Elsevier–period Ltd. vary in both construction and typology. Three weather scenarios (low, medium, high) and three district © 2017 The Authors. Published by Elsevier Ltd. committee of the scientific committee of the CISBAT 2017 International Peer-review under responsibility of the scientific renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, Conference obtained heat demand values were Peer-review under responsibility of the scientific committee of the CISBAT 2017 International – Future Buildings Keywords: Power Grid in the Beijing-Tianjin-Tangshan area,Smog Air Pollution,Air Source Heat Pump,Rural Space Heating,Power peak load& Conference – Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale. compared with results from afrom dynamic heat demand model, previously developed and validated by the authors. Districts – Energy Efficiency Nano to Urban Scale shifting The results showed that when only weather change is considered, the margin of error could be acceptable for some applications Keywords: Grid indemand the Beijing-Tianjin-Tangshan area,Smog Air Pollution,Air Source Heat Pump,Rural Space Heating,Power peak load (the errorPower in annual was lower than 20% for all weather scenarios considered). However, after introducing renovation shifting scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. author. Tel.: +8618800100881; . ©Corresponding 2017 The Authors. Published by Elsevier Ltd. E-mail address: [email protected] Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +8618800100881; . Cooling. * 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. E-mail address: [email protected] Peer-review under responsibility of the scientific committee of the CISBAT 2017 International Conference – Future Buildings & Districts – Keywords: Heat demand; Forecast; Climate change Energy Efficiency from Nano to Urban Scale. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the CISBAT 2017 International Conference – Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the CISBAT 2017 International Conference – Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale 10.1016/j.egypro.2017.07.361 632 2 Hui Le et al. / Energy Procedia 122 (2017) 631–636 Hui Le et al. / Energy Procedia 00 (2017) 000–000 1. Introduction The frequency of severe haze is much higher in winter than in the other three seasons in north China. In addition to climate factors, one of the main reasons for this pollution lies in a large number of air pollutant emissions caused by coal-fueled heating in rural areas.  Therefore one of the key points to mitigate the haze is to replace the scattered coal used for rural space heating. Moreover, shifting power peak load restricts the development of renewable energy. Because of the lack of flexible and effective means for shifting power peak load, wind power loss in China can be between 20% and 30% at present. In addition, large-scale promotion of photoelectricity is difficult due to the restricted grid access. 2. Methods Based on preliminary studies , we put forward the use of ASHP-AH (Air Source Heat Pump Air Heaters) for heating, which can realize clean heating in rural areas and enhance the efficiency with regard to shifting power peak load of the power grid. Driven by electricity, the ASHP-AH not only causes no emission of pollutants, but it can also utilize wind and light energy to improve new energy efficiency. The two-stage compression system increases heating capability and reliability in ambient conditions even down to -30 °C. Its COP can be up to 2.0 at ambient temperature T=-20°C , and 3.6 at ambient temperature T=7℃. Meanwhile, the ASHP-AH eliminates the sensation of draft and reduces the longitudinal temperature gradient by downside air supply. When power load is lowest, as original power demand at 4 am in Fig4, a part of ASHP-AH becomes operational for heating and the consumption of power grid electricity increases. When the power load reaches the peak, as original power demand at 9 am in Fig.4, a part of ASHP-AH stops, thus decreasing the consumption of power grid electricity, and in the meantime the indoor thermal environment is maintained by using the thermal inertia of the building itself. So we can regard the huge thermal inertia of the building as a massive storage body, providing a flexible and effective means for power peak load shifting. More specifically, a controller that can accept commands from a Power Grid Dispatching Center is installed in each ASHP-AH. The controller can be operated in one of the following three states: forced on, forced off, and controllable by users, which can be issued to a certain amount of ASHP-AH according to the peak load variation of the grid load, the wind power and light power conditions. When the ASHP-AH is forced to run or to stop, the power grid company will give economic compensation to users based on their contribution to power peak load shifting. In Beijing suburbs, each household needs 3 units at an installation cost of 4000 yuan / unit. The indoor temperature can vary from18°C to 28°C , and not lower than 15°C during the coldest period. The HSPF (Heating Seasonal Performance Factor) is between 3.2 and 3.5; and the power consumption during the heating season per unit floor area is 16.9-33.7 kWh/m2. By now, this system has been installed in more than 200 rural households. 3. Simulation 3.1. Model &ASHP-AH operating conditions Take an ASHP-AH used for space heating and power peak load shifting for example, and suppose that there are 6 million farmer households in the Beijing-Tianjin-Hebei Region, with a house area of 60m2 per household and a heating period from 15th November to 15th March. The power capacity of ASHP-AH in each household is 2.7kW, therefore the total installed capacity is 16.2million kW. DeST (a building energy simulation software ) was used to predict building load. There are 188 parallel power plants whose capacity is 300MW in Beijing-Tianjin-Tangshan area. ASHP-AH was adopted as a tool for power peak load shifting of virtual power plants. And we propose to show you the simulative ASHP-AH operating conditions on 3 typical days. Hui Le et al. / Energy Procedia 122 (2017) 631–636 Hui Le et al. / Energy Procedia 00 (2017) 000–000 Fig. 1 ASHP-AH operating conditions on Nov. 15th 633 3 Fig.2 ASHP-AH operating conditions on Dec. 25th Fig. 1 shows the typical operating conditions of ASHP-AH on 15th November at the beginning of winter. The Xaxis means 24 hours, the Y-axis means the 6 million farmer households in the Beijing-Tianjin-Hebei Region, a blue column represents the number of forced off users, an orange column represents the number of forced on users, a gray column represents the number of free users. Taking the operating condition at 1 am as an example, due to low electricity consumption at night, a part of the air source heat pump needs to be opened to fill the valley; therefore during this time the number of forced open users is more than 200 million, while at 9am more than 400 million users are forced off due to high electricity consumption. At the beginning of winter, the average forced open time is 5.4h and averaged forced close time is 1.8h per day per household. Fig. 2 shows the typical operating conditions of ASHP-AH in the middle of winter. As the outdoor temperature is relatively low, the heat inertia of the build is used to maintain the indoor temperature. It can be seen from simulation results that each household only needs less than 3h forced off time to maintain the indoor temperature within a reasonable range, which ASHP-AH can be controlled by the control center. The average forced on period is 6.2h, and the average forced off time is 7.1h per household per day. Fig3. ASHP-AH operating condition on Jan. 24th Fig.4 Generation curve of the heat pumps Fig.3 shows the typical operating conditions of ASHP-AH at the end of winter. During the day a certain number of air source heat pumps are shut down to mitigate the peak load. During this time, the control center will arrange forced off zones to ensure that not all pumps in every household are forced off longer than 3 hours, to ensure that the indoor temperature of a farmer’s house is within the comfort range. The average forced open time is 4h and the average forced off time is 2.9h per household per day. Fig.4 shows the generation curve after peak load shifting of the heat pumps, the blue curve is the original generation curve in the Beijing-Tianjin-Tangshan area, and the red curve is the ideal generation curve after using ASHP-AH for heating of rural houses. In Fig.5, the blue curve indicates the variation of room temperature, whose figures correspond to the vertical coordinates on the left. The red curve corresponds to users ‘forced on’ and ‘forced off’. 1 represents ‘forced on’ and 0 represents ‘forced off’. The green curve corresponds to users who freely control, the corresponding heat-supply corresponds to the heating load demand ratio on the right, ranging from 0 to 1. Hui Le et al. / Energy Procedia 122 (2017) 631–636 Hui Le et al. / Energy Procedia 00 (2017) 000–000 634 4 Fig. 5 Beginning of winter, from November.20th to 22th Fig.6 Middle of winter, from January.4th to 5th Fig.5 depicts the typical indoor air temperature variation from 20th November to 22th November for 3 consecutive days in the early cold period. It can be seen that the indoor air temperature is relatively high in early winter, within 18 ~ 22°C , while the load of ASHP-AH is relatively low. Fig. 6 depicts the typical indoor air temperature variation from 4th to 5th in January for 3 consecutive days in the middle of winter. The lowest indoor air temperature is not lower than 15°C (the designed indoor temperature of rural residential in freezing areas and cold areas), and the load of ASHP-AH in the middle of winter is relatively high. The “forced on” time increases due to the relatively low outdoor air temperature. Table 1. Statistics of forced on/off hours in heating season Forced on hours(h/day) Forced off hours(h/day) Beginning of winter 5.4 18 Middle of winter 6.2 7.1 End of winter 4 2.9 Note: average forced hours: on/off hour= 8.9h/day；on hours = 5.2h/day；off hours = 3.7h/day；Total electricity consumptions= 3839kWh Fig.7 Operation of the power plant in whole heating seasons Fig.8 Operation of the power plant in transitional period in winter The blue curve in Fig. 7 corresponds to the power supply curve before peak load adjustment of air source heat pumps, showing a great fluctuation; and the orange curve to that after the adjustment. The power used during the valley period is 75% of that in the peak period, with a variation of over 10 million kW. After taking advantage of an air source heat pump, the power plant is capable of realizing stable operation in the whole day; and can satisfy heating demand simply by turning on or turning off a certain number of machines. In this way, the power plant can operate at full load. This method can not only decrease the coal consumption for power plant, but also improve the efficiency of the power plant. Meanwhile, this method can decrease the frequency of starting/shutting of the machine and prolong the service life of the machine. As shown in Fig.8, the heating demands can be satisfied by putting a number of units into operation in the transition from the early cold period to severe winter, and shutting down some in the transition from severe cold period to the end of the cold period. Hui Le et al. / Energy Procedia 122 (2017) 631–636 Hui Le et al. / Energy Procedia 00 (2017) 000–000 635 5 3.2. Power consumption analysis Table 2. Power consumption in the whole heating season: Current After using ASHP-AH Electricity consumption except for heating pumps（100 million kWh） 1307 1307 Electricity Heating pumps（100 million kWh） 0 231 In total（100 million kWh） 1307 1538 Coal Power plant（10thousand tce） 4375 5011 consumption Rural heating（10thousand tce） 1572 0 Rural heating（10thousand tce） 5947 5011 In total（10thousand tce） 335 326 Using ASHP-AH to adjust electric peaks and valleys, we can effectively adjust the peak-valley variation of the power grid load, and put wind power into the power grid to partially replace coal-fueled power which helps to decrease the average coal consumption for power generation from 335gce/kWh to 326gce/kWh and save 9.36 million tce coal. As a result, the emissions caused by coal consumption may be reduced by 45%. 3.3. Economic analysis The cost for this new method is estimated as follows: each household needs 12K RMB to install the 3 units of ASHP-AH, 1560 RMB for coal-fueled heating in a heating season, and 1919RMB for electricity (suppose the price is 0.5RMB/ kWh) in the whole heating season. Due to generation efficiency enhancement with this method, users can obtain a subsidy 720RMB (according to simulation data) in a whole heating season, which means that each only has to pay 1217RMB for heating. Therefore, compared with coal-fueled heating, this methods provides not only a better room environment but also cheaper heating. 4. Experiment To verify the feasibility and effectiveness of this method, a demonstration project was carried out in the Fangshan District, Beijing, with 88 ASHP-AH installed for a number of households. Through the entire heating season in the test, it can be confirmed that the use of ASHP heating can indeed meet the heating demands of farmers and serve as a virtual peak shifting power plant. Fig.9 Operating conditions on coldest days in heating season Fig.10 The test of thermal inertia of building Hui Le et al. / Energy Procedia 122 (2017) 631–636 Hui Le et al. / Energy Procedia 00 (2017) 000–000 636 6 4.1. Meet the heating needs It can be found in Fig.9 that, from 20th January to 24th January, 2017, the outdoor temperature varied from -10.6°C to 3.5°C with an average temperature of -3.9°C . For rooms without heating, the average indoor temperature is 10.2 ℃, while for rooms with ASHP-AH, open for a certain time, the daytime indoor minimum temperature is not lower than 14°C. 4.2. Use as virtual power peak load shifting plant The test results on building thermal inertia is shown in Fig. 10. In the test, the room was heated to 25°C by the ASHP-AH and then cooled down naturally. Due to the thermal inertia of building, when average outdoor temperature was 2°C , the temperature indoors was higher than 15°C even if the pump was turned off for more than 10 hours, which demonstrates that it is possible to utilize the mass building thermal inertia to store energy. 4.3. Actual statistics of energy consumption of ASHP-AH Heating area/(m2) Number of main heating room Table 2. Power consumption in the whole heating season: Electricity Average Electricity consumption of consumption in electricity heating heating consumption /(RMB) season(kWh) (kWh/m2) Heating electricity per unit area（RMB/m2） 1# 62 4 1587.0 25.6 783.8 12.6 2# 43 3 1497.7 34.8 591.5 13.8 3# 79 4 11269.9 16.1 527.9 6.7 4# 124 3 3594.4 29.0 835.0 6.7 5# 225 1 757.1 30.3 280.6 11.2 6# 90 3 2534.2 28．2 1001.1 11.1 7# 160 7 7070.8 44.2 2705.4 16.9 5. Conclusions and Outlook In conclusion, ASHP-AH is a very good choice to replace rural coal-fueled heating with electricity, for it can eliminate serious pollution caused by scattered coal consumption for heating during winter, significantly alleviate occurrence of haze, improve farmers’ indoor comfort in winter and lower their economic burden. In addition, it also can be used as a "virtual peaking power plant" through active adjustment to achieve a wide range of power peak load shifting, significantly improve the efficiency of coal-fueled power plants, improve the current inefficient operation of power plants, eliminate bottlenecks in wind power and photovoltaic power network access, and promote the development of renewable energy. References  X. Ma, Z. Liu, X. Zhao, L. Tian, and T. Wang, “The Spatial and Temporal Variation of Haze and Its Relativity in the Beijing-Tianjin-Hebei Region.,” Reg. Res. Dev., vol. 2, pp. 134–138, 2016.  G. 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