Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

1. 서 론
2. 배경이론
    2.1 영농형 태양광 시스템
    2.2 농업에서의 의사결정지원시스템
3. 영농형 태양광 시스템 설계를 위한 의사결정지원시스템
    3.1 모바일 클라이언트 모듈
    3.2 의사결정 지원 모듈
4. 실 험
    4.1 전력 발전량 예측 모델 검증
    4.2 작물 생산량 예측 모델 검증
    4.3 실험 결과
5. 결 론
References

• Youngjin Kim(동국대학교 산업시스템공학과) | 김영진
• Junyong So(동국대학교 산업시스템공학과) | 소준용
• Yeongjae On(동국대학교 산업시스템공학과) | 온영재
• Jaeyoon Lee(동국대학교 산업시스템공학과) | 이재윤
• Sojung Kim(동국대학교 산업시스템공학과) | 김소정 Corresponding Author