The building model, used in the design study, is 10 m width, 40 m length and 40 m height (=10 stories) [34] with 40 households [35] . The BIPV system has considered on the roof/top of the building and a FC using electrolytic H₂ produced when the surplus power from PV has been available [1] .

The power generated by PV system is calculated by using the following equation [36] :

where E_PV is hourly electric power of PV system (kWh), H is hourly amount of solar radiation (kWh/m²), K is power generation loss factor (−), P is system capacity of PV (kW), 1 is solar radiation under standard state (AM1.5, hourly solar radiation: 1 kWh/m², module temperature: 25 degree Celsius) (kW/m²). The instantaneous solar radiation data by 10 sec of the reference [32] are integrated as hourly data for calculating the hourly electric power of PV system.

In this study, the high-performance PV P250a Plus produced by Panasonic has been considered. This module has conversion efficiency and maximum power rating per module is 19.5% and 250 W [37] . The size of PV module is 1580 mm × 812 mm × 35 mm. P has been calculated by installing this PV module on the roof of the building model, which is 75 kW_p (=300 solar modules). To calculate K, the performance value of state-of-the-art commercial devise is used. K is calculated by using the following equation:

where K_p is power conversion efficiency of power conditioner (−), K_m is correction factor decided by module temperature (−), K_i is power generation loss by interconnecting and dirty of module surface (−). In this study, K_p and K_i are set at 0.945 and 0.95, respectively. K_p is assumed by referring to the performance of commercial power conditioning device VBPC259B3 manufactured by Panasonic [38] . K_m is calculated by the following equation:

where T_m is PV module temperature (degree Celsius), T_s is temperature under standard test condition (=25 degree Celsius) (degree Celsius), C is temperature correction factor which is 0.35 [39] (%/degree Celsius). The temperature characteristics of PV module which is adopted for this study are referred. T_m is calculated by using the following equation [40] :

where T_a is ambient air temperature (degree Celsius), U_m is wind velocity over module of PV (m/s). In this equation, the convection heat transfer by wind around the PV module is considered.

The meteorological data, such as solar radiation, the ambient air temperature, and wind velocity of some cities in Japan have been taken from the data base of the project “PV300” during the period from August, 2013 to July, 2014 [32] . Table 1 has listed a sample of PV300 data, which shows the data of air temperature and amount of horizontal solar radiation at 10 sec intervals on 1^st August, 2013 for Tsu in Japan. According to the previous study [1] , the optimum tilt angle of solar panel installed on a roof/top of the building is 0 degree, resulting that the horizontal solar radiation has been used for calculating the power generated by the PV system in this study.

In this design study, it has been assumed that the surplus power generated by the PV system over the electricity demand of households [33] living in the considered building model, will be used for electrolytic H₂ production (i.e. long term energy storage in the form of electrolytic H₂). To optimize the size of BIPV system, number of households has been varied by 40, 20, 16 and 12 which correspond to 10, 5, 4 and 3 stories of the building, respectively. In this study, the building which has 4 households per floor is assumed. Then, the multiple number of 4 is based for assessment. To keep a building structure, the lowest limit of stories is set 3 which is the low height class building, indicating 12 households. The Type-S electrolyzer manufactured by IHT [41] [42] whose H₂ production rate, power consumption and electrolysis efficiency are 760 Nm³/h, 4.45 kHW/ Nm³ and 79.5%, have been used in this design study. The amount of electrolytic

H₂ could be produced by the surplus power generated from the PV system is calculated by the following equation [1] :

where is amount of electrolytic H₂ produced (Nm³), E_s is surplus power generated by PV system (kWh), P_e is power consumption (kWh/Nm³), is electrolysis efficiency (−). In this study, it is assumed that the electrolyzer can be operated following the power generation characteristics of PV system every time and the produced H₂ can be stored as well as used instantaneously.

It has been assumed that the H₂ produced by the electolyzer would be used to generate power through a polymer electrolyte fuel cell (PEFC) system [3] . H₂ is converted into electricity by FC following the below equation:

where is power generation efficiency of latest PEFC stationary system based on lower heating value (=0.39) [43] , Q is lower heating value of H₂ (=242) (kJ/mol). It is assumed that the energy loss for operating pump to preserve and provide gases is ignored.

In this study, a monthly self-sufficiency rate of the proposed combination system consisting of the PV and FC has been investigated for Tsu (Latitude: 34.43˚N, Longitude: 136.30˚E), Yokkaichi (Latitude: 34.57˚N, Longitude: 136.37˚E), Kuwana (Latitude: 35.03˚N, Longitude: 136.41˚E), Ise (Latitude: 34.29˚N, Longitude: 136.42˚E) and Owase (Latitude: 34.04˚N, Longitude: 136.11˚E). They are the main cities in Mie prefecture, Japan. The self-sufficiency rate is defined as the power supplied (from the combined PV and FC system) to the electricity demand of the households living in the building. The hourly time change in the self-sufficiency rate in the day, when the daily mean amount of horizontal solar radiation per month has been obtained and estimated.

As described in earlier sections, this study has investigated the power production from the PV system using the meteorological data base of PV300 [32] including air temperature, solar intensity and wind speed at 10 sec intervals. Since the electricity demand of households [33] is available as hourly data, the power production from the PV system is summarized as hourly data by integrating the instantaneous data available at 10 sec intervals.

As an example, Table 2 has listed the hourly power from PV system (installed in Tsu for a year) which is shown to investigate the seasonal characteristics. In this table, the hourly time change in power of PV system in the day when the daily mean amount of horizontal solar radiation per month has been obtained and estimated. From this table, the hourly power of PV system increases from the morning up to the noon and decreases from the noon up to the evening as expected. In addition, it is obvious that the hourly power of PV system is higher in spring and summer, while it is lower in autumn and winter. The data shown in Table 2 has been summed for daily data and it has been multiplied by the total days for each month for using as monthly data. The monthly power production from the PV system is shown in Table 3 which is shown to investigate the seasonal and local characteristics. It has been observed that the monthly power of the PV system is higher in spring and summer, while it is lower in autumn and winter irrespective of the cities.

Table 4 has listed the hourly electricity demand of 40 households for a year which is shown to investigate the seasonal characteristics. In this study, the electricity demand profile, which depends on the city are not considered. It means that the same electricity demand profile has been used for the five cities as design study. When considering the electricity demand profile of other number of households, the data shown in Table 4 have been recalculated. It has been observed that the hourly electricity demand increases from the morning and keeps almost a constant value during a day. After that, the hourly electricity demand increases rapidly from the evening and keeps almost a constant value up to the midnight. In addition, it is obvious that the electricity demand is higher in

summer and winter, while it is lower in spring and autumn. The data shown in Table 4 have been summed as daily data and it was multiplied by the total days for each month as monthly data.

Table 5 has listed the hourly power production for a year from the FC system, assumed to be installed in Tsu, which has been calculated by using the surplus power of PV system and the Equations (5) and (6). According to Table 2 and Table 4, the surplus hourly power of the PV system is high during the daytime, especially at the noon, while it is low from the evening to the early morning. When the hourly self-sufficiency rate of PV system is over 100 %, it means that the FC system has the capacity to generate the power due to the surplus power of PV system or the surplus energy can be stored in the form of electrolytic H₂. In this study, it has been assumed that the surplus power of PV system can be utilized by the water electrolysis immediately and be stored as electrolytic H₂. It has been also assumed that the stored electrolytic H₂ can be utilized in the FC system for fulfilling the shortage of energy during the required time. In Table 5, hourly power productions from the FC system are used for finding daily power production from the FC system and it has been multiplied by the total monthly days for finding monthly power production from the FC system. The monthly power production profile of the FC system has been given in Table 6.

Table 6 has listed the monthly power production from the FC system which is shown to investigate the seasonal and locational characteristics. Figure 1 has shown the monthly self-sufficiency rate of the FC system which is also shown to investigate the seasonal and locational characteristics. The self-sufficiency rate is

calculated by dividing the power produced by the FC system by the electricity demand, which is not covered by the PV system. If the self-sufficiency rate of the FC system is over 100%, then the proposed BIPV system with the FC system utilizing electrolytic H₂ generated by water electrolysis can cover the electricity demand of households living in the building.

According to Table 6, the monthly power of the FC system is higher in spring and summer, while it is lower in autumn and winter irrespective of cities. Also, it follows the power generation profile of the PV system.

It has been seen from Figure 1 that the monthly self-sufficiency rate of the FC system is below 100% irrespective of the cities. The annual self-sufficiency rate of the FC system assumed to be installed in the Tsu, Yokkaichi, Kuwana, Ise and Owase are 29%, 23%, 25%, 19% and 22%, respectively. Therefore, the proposed BIPV system with FC system utilizing the electrolytic H₂ generated by water electrolysis can’t cover the electricity demand of 40 households living in the building. This study has investigated the optimum households number per same installment area of PV array in the next section.

The households number is changed to investigate the proper households number per same installment area of solar array on the roof/top of building. Figures 2-4 have shown the monthly self-sufficiency rate of FC system assumed to be installed in Tsu, Yokkaichi, Kuwana, Ise and Owase for 20, 16 and 12 households cases, where the stories of buildings are 5, 4 and 3, respectively. These figures are shown to investigate the seasonal and locational characteristics under different households conditions.

It has been observed through Figures 2-4, the self-sufficiency rate of FC system is higher with decreasing households number, resulting that the self-suffi- ciency rate of FC system which is over 100% can be seen in spring and summer.

The annual self-sufficiency rate of the FC system assumed to be installed in Tsu, Yokkaichi, Kuwana, Ise and Owase for 20 households design case are 74%, 60%, 63%, 52% and 61%, respectively. The annual self-sufficiency rate of the FC system assumed to be installed in Tsu, Yokkaichi, Kuwana, Ise and Owase for 16 households design case are 98%, 79%, 83%, 69% and 81%, respectively. The annual self-sufficiency rate of the FC system assumed to be installed in Tsu, Yokkaichi, Kuwana, Ise and Owase for 12 households design case are 138%, 111%, 117%, 98% and 115%, respectively. From these results, 12 households are more suitable for full cover of the electricity demand by the combined system of PV and FC. Though it is expected that the smaller number of households below 12 indicates the larger self-sufficiency, it is necessary to consider the large electrolytic H₂ storage system for the excess power generated by the PV system instead. In addition, it is assumed that one story consists of 4 households. Consequently, this design study decides that 12 households is the optimum for the proposed BIPV system with FC system.

The relationship between the households number and self-sufficiency rate of FC system per solar PV installation area has been shown in Figure 5. It is observed that the relationship between the households number and self-sufficiency rate of FC system per solar PV installation area can be expressed by the exponential curve well. If the coefficient of the exponential curve is high, e.g. 0.6127 in Tsu case, it means that the self-sufficiency rate of FC system per solar PV installation area is high. Therefore, we can recognize that Tsu is more suitable for the installment of proposed BIPV system. Tsu is located at the center in Mie prefecture and obtain the large amount of solar radiation. In addition, the wind condition is also good to prevent the elevation of PV panel temperature since the mountain ranges are located at the northwest of Tsu. Consequently, the self-sufficiency rate for Tsu is the largest. On the other hand, since Ise is located in the southeast area in Mie prefecture and it is easy to rain, the amount of solar

radiation is smaller than the other cities. Therefore, the self-sufficiency rate for Ise is the smallest. Owase is also located in the south area in Mie prefecture and it is easy to rain, resulting that the self-sufficiency rate becomes smaller. In the future work, the energy network system consisting of several BIPV system assumed to be installed in several cities will be investigated in order to cover the electricity demand of each other through H₂ transportation/infrastructure.