Integrated Management Model for Photovoltaic Projects: Optimizing Control

Abstract

The management of photovoltaic (PV) projects is characterized by high technical and logistical complexity, coupled with resource volatility. This study addresses the critical fragmentation among planning, execution, and financial control processes, which leads to information silos, administrative burden on project managers, and delayed strategic decisions, ultimately compromising project profitability. The main objective was to develop and propose a conceptual integrated management model for the PV sector, operationalized via a prototype tool in Microsoft Excel, to effectively articulate these three dimensions. A qualitative methodology was employed, centered on a single case study within a sector company.
Data collection involved documentary analysis (10 projects) and direct observation of project managers' work. The critical literature review reveals that while robust project management frameworks (PMBOK, PRINCE2) and control methodologies (Earned Value Management - EVM) are available, their practical application and integration within the specific PV context remain underexplored, indicating a significant research gap.
The proposed model synthesizes and adapts the principles of PMBOK, EVM metrics, and Balanced Scorecard (BSC) perspectives to the sector's specificities. It is concluded that implementing this integrated model, supported by a real-time monitoring tool, significantly enhances performance visibility, deviation anticipation, and decision-making effectiveness, thereby strengthening the economic sustainability of PV companies.
Success will be evaluated through specific KPIs that reflect the effectiveness of the integration. To ensure sustainability and continuous improvement, the following feedback mechanisms will be implemented:
• Quarterly Performance Reviews
• Lessons Learned Reports
• User Satisfaction Surveys
• Technological Evolution
This research contributes an applied conceptual framework and a phased implementation plan, proposing future research lines for the empirical validation of the model in other contexts.