Photovoltaic generation systems have been attracting attention in recent years as a countermeasure against the depletion of fossil fuels and global warming. Since PV is affected by the weather and PV power changes rapidly, there is a risk of adversely affect the power grid. To solve this problem, there is a method for predicting solar irradiance using the all-sky image. The method of previous research estimates the solar irradiance from all-sky images, and then predicts the solar irradiance by inputting all-sky images and the estimated solar irradiance into a convolutional neural network (CNN). This study evaluates the impact of the pixel size of all-sky images on estimation accuracy in a CNN-based solar irradiance estimation method.

This paper proposes a fluctuation determination method based on CNN. Previous research has reported that prediction accuracy for solar irradiance can be improved by learning solar irradiance prediction models using data with fluctuations and data without fluctuations, respectively and then switching the solar irradiance prediction model according to the fluctuation determination model. However, the fluctuation determination model is in an ideal state. This paper first estimates cloud coverage from all-sky images. Then, the fluctuation determination model based on CNN that uses all-sky images and cloud coverage as input is proposed. As a result of fluctuation determination model inputting cloud coverage, true negative rate was low as 10.1% although accuracy was high as 92.4%. The prediction accuracy for 15 minutes ahead solar irradiance was improved 5.4% compared to the conventional method.

We have been evaluating the optical flow from all-sky images to determine the direction of cloud flow in order to predict solar power generation. However, the methods we have used in our development to date have sometimes failed to find the correct direction. In addition, when the cloud flow was assumed to be in one or two directions, it was possible to determine the direction, but not to determine whether the cloud flow was in one or two directions. Therefore, this study attempted to select a more appropriate optical flow method and develop a method to determine the number of cloud flow directions using the circular standard deviation.

We have been developing methods of short-time solar radiation forecast using meteorological satellite imagery. Changes in solar radiation are mainly due to cloud movement up to a few hours ahead, but as the forecast time becomes longer, the effect of cloud formation and dissipation becomes more significant. In weather forecasting, there is always inherent uncertainty, and probabilistic predictions are crucial for assessing risks and making informed decisions. In this study, we report on our efforts to advance solar radiation forecasting technology under the NEDO project regarding the above issues.

In recent years, the use of renewable energy has been attracting attention, and forecasting the supply and demand of solar power generation has become indispensable. Our research group is constructing a system to predict horizontal solar radiation intensity by monitoring the behavior of cloud shadows. In this study, a model to estimate the amount of electricity generated from the predicted horizontal solar radiation intensity was constructed using an artificial neural network, and the training parameters were examined.

In order to provide political supports effectively, future installation of PV should be properly assumed in terms of regional location and specific site. The assumption on future PV distribution can be improved by considering the current status of PV installation in various categories. Therefore, this study investigates the relationship between the statistics of the approved capacity of PV under the feed-in tariff (FIT) and the land use statistics based on mesh data.

The use of solar radiation forecast information is essential for the operation of PV systems. Currently, three-hourly averages of solar radiation predictions are available from the Japan Meteorological Agency's MEPS (Meso-scale Ensemble Prediction System). For more detailed energy management, one-hour values with finer temporal granularity are effective.

In this paper, we propose a new method to estimate one-hour values from three-hour MEPS averages by machine learning based on JIT Modeling. The validity of the proposed method is demonstrated by comparing it with a simplified method that uses the prorated amount of exoatmospheric solar radiation.

In power systems where large amounts of photovoltaic power generation have been installed, operational planning is based on next-day solar radiation forecasts. In order to realize efficient and stable power system operation, advanced next-day solar radiation forecasting is necessary, and forecasts must not only have average accuracy but also be able to control the risk of rare large outages. In this study, a multiple solar radiation forecast model using ensemble forecast data was constructed by machine learning, and a forecast model that can both improve the average accuracy and suppress the risk of large over-estimation was investigated.

The purpose of our research to demonstrate creation flexibility by means of headroom control for photovoltaic power generation technology. This paper reports the results of an evaluation of the potential for flexibility of PV.

Fe/N/C type oxygen reduction catalysts were prepared using nitrogen-doped KB to increase the activity of non-platinum oxygen reduction catalysts. The results showed that nitrogen doping increased the surface nitrogen concentration of the catalyst by a factor of up to 1.85. The onset potential where oxygen reduction current flows (@0.1 mA mg⁻¹) increased up to 0.031 V, and XPS measurements suggested that the Fe-N type nitrogen was the active site, whereas the 4e^- electron reduction efficiencies of the catalysts decreased by 4~26%.

Fe/N/C oxygen reduction catalysts have problems with low oxygen reduction reaction (ORR) activity and durability, as well as a considerable consumption of time and energy during synthesis. The objective of this study is to improve the activity and the energy efficiency of Fe/N/C catalysts in the synthesis process through the application of microwave synthesis. The precursors were prepared using microwave irradiation as an alternative to heat under reflux, followed by subsequent heat-treatments. The ORR current and 4e⁻ efficiency for the catalysts prepared by a microwave method were 1.2 and 1.1 times higher than those prepared by the reflux method, respectively. It is suggested that the microwave method increased active sites and improved activity of catalyst. The time required for synthesis of the Fe/N/C catalysts was reduced to one-third by the microwave method.

Carbon supports were synthesized the heat-treatment of paper processed with methanesulfonic acid, and non-platinum oxygen reduction catalysts were prepared by using a two-step heat-treatment process with a SUS-316 airtight container and a quartz boat. The diffusion limiting current using the catalyst made from toilet paper was higher than those made from the other papers, and the onset potential where ORR current flows (0.1 mA mg⁻¹) improved by approximately 0.02 V compared to that made from the conventional Ketjenblack^®. It was revealed that the use of the microwave (MW) method further enhanced the onset potential, achieving 0.909 V vs. RHE.

We have reported on the development of a Ru/TiO₂ catalyst, aiming for the practical conversion of natural energy into ammonia via electrolytic synthesis. In this study, we improved the structure of the electrolytic synthesis cell to enhance current values and stability. The study was also focused on examining the active sites of the catalyst, comparing the nitrogen reduction abilities of the Ru/TiO₂ catalyst, which contains a Ti-O-Ru bond, with the Ru/KB/TiO₂ catalyst, which lacks this bond, alongside an evaluation of their pH dependencies. Enhancing the adhesion between the Nafion^® membrane and carbon paper led to a significant improvement, increasing current values by up to 100 times. Both catalysts exhibited increased ammonia production rates and Faraday efficiencies around at pH 7. Notably, the Ru/TiO₂/CP catalyst showed an ammonia production rate and Faraday efficiency that were 23 times higher, highlighting the functional role of the Ru-O-Ti bond as a catalytic active site.

Several solar thermochemical reactors have been developed to split water by a two-step water-splitting cycle with redox metal oxide utilizing concentrated solar thermal energy in sunbelt region, including a windowed solar reactor using a reactive foam device made of metal oxide. In this study, small foam devices of magnesio-ferrite were fabricated and tested on their reaction performances in a lab-scale windowed reactor using a 3kW_th sun simulator. The magnesio-ferrite foams produced 2 - 3 times the amount of hydrogen in comparison to benchmark CeO₂ foam.

A two-step thermochemical water splitting cycle using a redox system of a metal oxide is one of the promising processes for converting concentrated solar high-temperature heat into clean hydrogen in sun-belt regions. Recently, Zhai et al. have shown that a poly cation oxide (Mg_0.25Ni_0.25Co_0.25Fe_0.25O_x or MNCFO) or a high entropy iron oxide reveals a greater reactivity for the two-step water splitting cycle than the benchmark ceria. In this work, we have discovered that Mn-containing high-entropy iron oxides have much greater reactivities than ceria and the MNCFO for the lower temperature cycles below 1200-1400˚C.

We study reduction reaction of Zinc Oxide toward generating sustainably Hydrogen energy. The heat required for the reaction is extracted from sunlight. Also, we used an election furnace for adjusting temperature to heat Zinc Oxide. This result in, we can investigate relationship between reduction of Zinc Oxide and temperature. We can know that reaction depends on temperature.

The purpose of this study is to establish a hydrogen production and reduction cycle using solar energy. The cycle is based on the redox system of zinc oxide. Sunlight is focused using a Fresnel lens and used as a heat source. When zinc oxide and carbon in a reaction tube are heated, the zinc oxide is reduced and zinc is generated. The zinc and water are then reacted to produce hydrogen. This time, we conducted an experiment using an electric furnace. Investigate the maximum hydrogen concentration when changing the water injection amount, zinc amount, and heating temperature.

This paper describes the results of experiments that simplified solar wood-biomass drying system with a small sun-room. Followings are found. In experiment, the maximum outlet-air temperature at solar collector became 30˚C. As a result, moisture content became 55%-w.b. to less than 20 %-w.b. in 4 days.

The moisture content in wood chips used in biomass boilers, which are made from thinned wood and waste wood, makes combustion difficult and reduces the calorific value. This study aims to reduce the moisture content of wood chips used in biomass boilers by irradiating them with sunlight, which is a renewable energy source, and by agitating them. As a result of these effects, the target value for reducing the moisture content of wood chips was achieved.

Facility horticulture generally uses fuel oil boilers for heating. Possible difficulty in continuing business due to soaring fuel oil prices. The objective is to reduce energy consumption using solar heat. Firstly, we measured the actual environment in the greenhouse. Secondly, the relationship between fruit quality and the environment was considered. Finally, conducted experiments to optimize the heat supply. High quality fruit was seen when average soil temperatures ranged from 24°C to 27°C. Soil temperature can be controlled by heater temperature and distance from the bed.

The purpose of this research is to optimally design building equipment systems based on the exergy concept in order to realize ZEB. We will construct a calculation model based on actual measurements for building equipment systems in which heat, which is low-quality energy, and electricity and fossil fuels, which are high-quality energy, enter and exit. In this paper, we report the results of constructing and examining a computational model for solar heat utilization systems.

To put cooling system used solar thermal energy for practical use, is not so easy, especially economically.

Desiccant dehumidifying system only for inlet air from ambient as ventilation was made and tested throughout a summer season. In addition, to improve air conditioning effect, air to air heat exchanger as to cooling air risen temperature with dehumidifying by silica gel was made Experimentally.

In order to investigate the possibility of net-zero energy in the central air-conditioning house, field measurement in the inhabited house equipped with the earth tube and solar photovoltaics system was conducted throughout 10 years. In this paper, measurement results of temperature and humidity, energy balance were analyzed, and long-time changes of indoor environment and effect of the earth tube, achievement of net-zero energy were described.

The effectiveness of passive design was evaluated and the realization of ZEH (Net Zero Energy House) was discussed for a detached wooden house designed using passive design for the realization of a decarbonized society in 2050. In this report, it is confirmed from the measurement data under actual residence that both comfort and energy saving are achieved by passive design and high airtightness and high thermal insulation performance.

To achieve net zero energy houses, it is necessary to install PV on the roof of houses. However, the electricity generated by photovoltaics have been required to be consumed in their houses. In this paper, we conducted an actual measurement survey of energy self-sufficient house installed with large-capacity storage batteries and daytime operation of heat pump water heater. As a result, the electricity self-sufficiency rate of an energy self-sufficient house was 58%, and it is clear that more than half of the electricity consumption could be covered by photovoltaics generation.

In resent year, the electricity generated by photovoltaics have been required to be consumed in their houses. By sharing electricity among multiple houses, more electricity generation can be self-consumption. In this paper, we analyze the sensitivity of self-consumption rate of photovoltaics and self-sufficiency rate of electricity to storage battery control parameters when sharing electricity among multiple houses. In addition, based on the actual measurement results, we report on the improvement effects of the previous two items and the performance evaluation results of each storage battery.

This study investigated the effect that adding a photovoltaic solar cell (PV) to a structured‐core transparent vacuum insulation panel (TVIP) would have on the insulation performance on panel. This photovoltaic TVIP, PV‐TVIP for short, was measured in simulated summer and winter conditions by using a climate‐controlled chamber for temperature control, and a halogen light to simulate solar radiatoon at 1000 [W/m²]. The additional temperature increase caused by the normal electricity production of the PV was largely confined to increasing the temperature on the side of the TVIP that the PV was attached to, bringing no negative effect to the temperature on the other side. While issues with core material outgassing remain during hot temperature measurements, a temperature differential of approximately 18 [°C] was achieved between room temperature and ‐10 [°C] spaces by using a TVIP with a thermal conductivity value of approximately 0.024 [W/(m*K)].

This study clarified the summer indoor climate with passive ventilation and “open cooled (OC)” house in Tokyo. The room temperature and MRT in the OC house maintained around 25°C in all rooms with a single air conditioner, while the MRT was 1 to 1.5°C higher than the room temperature in the normal “closed-cooled (CC)” house. Although the air velocity in the OC house was significantly lower than that in the CC house, the occupant of the OC house felt a slight airflow, while the non-occupants felt almost no airflow, and were often neither hot nor cold, respectively. It was confirmed that the indoor climate of OC house is different from that of CC house.

Year-round measurement is being performed under actual living environment in LCCO₂ minus home which was built in Asahikawa-shi, Hokkaido. We confirmed the influence of occupants' living style on energy consumption. For heating and cooling, we clarified the degree to which heating and cooling energy consumption is affected by how residents seek thermal comfort. As for hot water supply, we confirmed that the use of hot water in the bath has a large effect on the energy consumption for hot water supply, and that there are also differences depending on the temperature at which hot water is used.

Using an inexpensive hybrid inverter manufactured overseas, we constructed an economical semi-off-grid system for residential use that is free from legal issues, and conducted a demonstration test. As a result, although there were no problems with single-phase three-wire operation during full-load backup in an all-electric home, the efficiency of the entire system was relatively low performance compared to commercially available products. The characteristics of the two systems (Converts single-phase 2-wire output to single-phase 3-wire using a transformer, Using split phase inverter) used in the experiment were clarified. However, no major practical problems were found.

A traditional timber house in a satoyama environment (Machida City, Tokyo) was renovated and a ventilation units utilizing solar heat, nocturnal radiation and geothermal heat was applied. Also, we focused hiroen as a thermal buffer space. In this reports, we confirmed from an overview of actual measurement date that the indoor thermal environment is generally as planned, and that the heating, cooling, and ventilation units are operating as planned.

In this study, we investigated Kunio Mayekawa’s environmental adjustment methods (Mayekawa’s methods), targeting Mayekawa Architecture in Hirosaki City. We researched the intentions of Maekawa's methods through literature and interviews. The purpose of this study is to verify the effectiveness of Maekawa’s methods through actual measurement and analysis of thermal and light environments.

Improvement of prediction accuracy is required for forecasting photovoltaics (PV) power outputs in a large area. If we can obtain the information of the recently PV installed area when we conduct forecasting, because we can clarify the area of weather forecasting information which we should to use, it conceivable that we can improve prediction accuracy. In this paper, we propose the method which estimates geographical distribution of installed PVs in the specific area from solar irradiance real-time estimation data and total PV power output data in the area. The estimation accuracy and the influence arising from the particle size of estimation are also reported.

Many cedar and cypress trees were planted in Japan for timber, but many of these have been left unattended and are causing various problems today. They have caused an increase in the pollen-affected population, a decrease in grassland, animal damage and adverse effects on vegetation. Another problem is the need for additional solar photovoltaics (PV) to achieve carbon neutrality, but there is little flat land in Japan, and suitable sites for PV installations is decreasing. It was therefore thought that these two problems might meet the need for photovoltaic installations. The idea was therefore to install PV installations in place of abandoned planted trees and to restore grasslands near the PVs. In order to explore this possibility, this paper conducted an actual survey of the area of planted trees in Fukui prefecture that were planted more than 50 years ago. As a result, it was found that approximately 84% of the trees in Fukui prefecture are currently planted trees that are 50 years old, indicating that planted trees cover a very large area and have great potential in terms of both power generation capacity and grassland restoration.

The recent extreme weather conditions have caused an increase in scattering damage to photovoltaic power generation facilities, mostly due to inadequate design of the supporting structure. In particular, the number of cases of foundation piles being pulled out due to strong winds, etc., is increasing, and if they are pulled out from their foundations, it could lead to extensive damage. Therefore, we have developed a reinforcement method using special anchors that can be installed even in narrow areas as a countermeasure against pulling out of foundation piles in existing power plants, which are considered to have many design flaws.

There is growing concern about the increasing power consumption of data centers (DC), to address, it is necessary to increase the use of renewable energy sources (RE). However, a significant challenge lies that RE output is variable. Therefore, CPU speed control to charge and discharge toward RE100%DC is proposed to address output fluctuations in this paper. Then, optimization simulations with the temperature constraints have been done to validate the effectiveness of this approach.

In this study, Fuzzy logic was applied to take into account the ambiguity of large and small labeling for the variables used to determine the amount of charge and discharge in the recharge/discharge control of storage batteries. The ratio of recharge/discharge to the available amount of recharge/discharge was output using the clear weather index, which indicates the degree of clear weather, and the remaining amount of storage batteries as input values. As a result, it was confirmed that the application of Fuzzy logic reduced the total amount of electricity exchanged with the grid.

In recent years, green base stations with storage batteries and photovoltaic (PV) power generation have been considered to improve environmental friendliness and disaster resistance in the operation of wireless communication base stations. As a measure to improve the economic efficiency of these green base stations, it is considered effective to participate in the DR (Demand Response) market and to provide electricity to other green base stations through self-wheeling by utilizing PV power. This paper presents a fundamental study of energy management methods aimed at reducing failures when participating in DR while conducting self-wheeling.

In recent years, a large penetration of PV into the power systems has raised concerns about the occurrence of grid congestion, in which active power flow into the transmission lines exceeds operational limits. In response, battery energy storage systems that are directly connected to the power systems are being introduced to reduce grid congestion.

This paper quantitatively analyzes the effect of battery energy storage systems on congestion reduction on the basis of the results of optimal power flow calculations based on PV output predicted by Meso-Scale Model GPV.

In recent years, with the spread of photovoltaic systems (PVSs) are becoming deterioration and failures that lead to accidents and fires are increasing, and reducing the cost of maintenance and inspections to prevent these problems is an issue. In this study, we propose a machine learning method using logistic regression analysis, which is a type of multivariate analysis and has a low computational load, with the aim of simplifying maintenance and inspection. In this presentation, we will report that we have verified the effectiveness of the proposed method by learning using measured data from a site of PVS.

We have been developing a system to diagnose DC problems in photovoltaic power generation facilities. This system diagnoses the health of bypass circuits, cell string circuits, and insulation performance of photovoltaic modules by measuring the electricity in each string. We have installed this system at an actual site and verified its various functions.

This study proposes a failure diagnosis method to detect failures of PV module connected in PV string. As a detection index, capacitor voltages after first and eighth flash light irradiation and output current at the end of the first flash light irradiation are used in the proposed method. To confirm the feasibility of the failure diagnosis method, the authors perform calculations and experiments. As a result, it is made clear that a specific factor of failures of PV modules can be identified based on capacitor voltages after first and eighth flash light irradiation and output current at the end of the first flash light irradiation.

With conventional technology, even if it is possible to discover whether there is an open fault bypass circuit in a string, it is difficult to pinpoint its location. When a voltage is applied in the direction in which the bypass circuit of the PV module operates, the temperature rises in the open fault PV cluster, and this is used to identify the fault position. The purpose of this study is to identify the location of open fault PV cluster. In this paper, we describe the effect of amplitude of the applied voltage across a string to identify the two open fault cluster in a string.

The purpose of this study is to investigate the long-term reliability of various photovoltaic (PV) technologies in Japan under humid subtropical climatic conditions. The performance ratio (PR) of five kinds of PV modules is estimated based on the power outputs of the PV arrays, backside module temperature and solar irradiance, which are measured at ten minutes interval over 12 years.

Although the curtailment of solar energy in Japan remains at an appropriate level by international comparison, it is often considered serious because of the possibility that the amount of lost energy generation due to curtailment may affect business operations. On the other hand, analysis of time-series data from more than 200 small-scale solar power plants compiled by the authors indicates that the amount of lost energy generation due to improper maintenance is not negligible and has reached a level more serious than curtailment at some power plants. This report evaluates the lost power generation from these two perspectives.