An advantage of solar-powered houses is the concurrent generation and consumption of power. However, the simultaneous power consumption of a solar-powered house tends to be lower than its actual load consumption. We aim to design a multi-agent system for exchanging the power value information within a solar-powered house and neighborhood in order to maximize simultaneous solar-derived power usage. This study purposes a priority order to determine the simultaneous solar-derived power usage procedure. Using the measurement data of a next-generation solar-powered house on a sunny day, we evaluate the estimation result of the domestic power balance and analyze the time series of each of the power variabilities. From the result, the three types of power usage are classified, and the four phases of the power capacity allocation are defined. We clarify the specific calculation procedure and indicate the availability of simultaneous solar-derived power usage by finding the optimum combination of the power capacity and the usage volume per hour. Finally, we estimate that the total value of available simultaneous solar-derived power usage is approximately 80% of the capacity in the solar-powered house and four hypothetical neighborhood houses, contributing to a drastic reduction in surplus power.

1. [1] International Energy Agency, “Technology roadmap – solar photovoltaic energy 2014,” pp. 7-17/32-40, 2014.
2. [2] Energy Efficiency and Conservation Division Agency for Natural Resources and Energy Ministry of Economy, Trade and Industry, “Definition of ZEH and future measures proposed by the ZEH roadmap examination committee,” 2015.
3. [3] International Energy Agency, “How2Guide for Smart Grids in Distribution Networks – Roadmap development and implementation,” pp. 5-11, 2015.
4. [4] Japan Photovoltaic Energy Association (JPEA), “Current status of Photovoltaic Power Generation – Fundamental revision and growth strategy,” 2019 (in Japanese).
5. [5] K. Nagasaka, “Development and Current State of Smart Grids: A Review,” J. Adv. Comput. Intell. Intell. Inform., Vol.21, No.1, pp. 49-58, 2017.
6. [6] E. Matallanas, J. Solórzano, M. Castillo-Cagigal, I. Navarro, E. Caamaño-Martín, M. Egido, and A. Gutiérrez, “Electrical energy balance contest in Solar Decathlon Europe 2012,” Energy and Buildings, Vol.83, pp. 36-43, 2014.
7. [7] E. Rodriguez-Ubinas, S. Rodriguez, K. Voss, and M. S. Todorovic, “Energy efficiency evaluation of zero energy houses,” Energy and Buildings, Vol.83, pp. 23-35, 2014.
8. [8] “Solar Decathlon Europe 2014 – Rules, Vol.5.0,” pp. 41-44, 2014.
9. [9] S. Tajima, S. Okada, and T. Kawase, “Efforts of Chiba University Team to the Solar Decathlon Europe 2014: Development of Net-Zero-Energy and Prefabrication House,” AIJ J. of Technology and Design, Vol.21, No.48, pp. 735-740, 2015 (in Japanese).
10. [10] T. Kawase, S. Tajima, H. Obara, R. Hazumi, and S. Nasu, “Solar Decathlon Europe 2014 – Chiba University Japan’s Challenge,” J. of Japan Solar Energy Society, Vol.40, No.6, pp. 53-61, 2015.
11. [11] S. Nasu and Y. Sugai, “Estimation of surplus power from energy efficient solar house,” Proc. of EcoDesign2015 Int. Symp. on Environmentally Conscious Design and Inverse Manufacturing, pp. 831-834, 2015.
12. [12] S. Nasu and Y. Sugai, “Evaluation of Simultaneous Consumption of Electrical Energy at Energy efficient Solar House,” Proc. of Electronics Goes Green 2016+ Int. Congress, 2016.
13. [13] S. Nasu, S. Tajima, and Y. Sugai, “Estimation of Maximum Simultaneous Electric Energy Consumption for Energy Efficient Solar Powered House,” Proc. of Grand Renewable Energy 2018 Int. Conf. and Exhibition, 2018.
14. [14] S. Nasu, S. Tajima, and Y. Sugai, “Calculation of surplus power of energy efficient solar powered prototype house for maximizing simultaneous electric power consumption in local,” Proc. of EcoDesign 2019, 2019.
15. [15] Y. Kishita and Y. Umeda, “Development of Japan’s Photovoltaic Deployment Scenarios in 2030,” Int. J. Automation Technol., Vol.11, No.4, pp. 583-591, 2017.
16. [16] S. D. Ramchurn, P. Vytelingum, A. Rogers, and N. Jennings, “Agent-Based Control for Decentralised Demand Side Management in the Smart Grid,” Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems, Vol.1, pp. 5-12, 2011.
17. [17] K. Kok, Z. Derzsi, J. Gordijn, M. Hommelberg, C. Warner, R. Kamphuis, and H. Akkermans, “Agent-Based Electricity Balancing with Distributed Energy Resources, A Multiperspective Case Study,” Proc. of the 41st Annual Hawaii Int. Conf. on System Sciences (HICSS 2008), 2008.
18. [18] T. Taniguchi, “Algorithm for Adaptive Intelligent Agent Trading Electric Power in Decentralized Autonomus Smart Grid – Analysis of Dynamics of Bottom-up Price Formation by Intelligent Power Router and Demand Response,” Trans. of the Japanese Society for Artificial Intelligence, Vol.28, No.1, pp. 77-87, 2013.
19. [19] T. Ito, S. Chakraborty, K. Otsuka, R. Kanamori, and K. Hara, “A Survey of Multi-Agents Research That Supports Future Societal Systems (2): Power Systems, and Wireless Sensor Networks,” J. of of Japanese Society for Artificial Intelligence, Vol.28, No.3, pp. 370-379, 2013.
20. [20] Solar Decathlon Europe 2014. http://www.solardecathlon2014.fr/en/ [Accessed September 20, 2017]
21. [21] K. Fujii, N. Morimoto, S. Miyazaki, and Y. Okabe, “Experimental Evaluations of Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions,” Information Processing Society of Japan Kansai Branch, B-03, 2015.