Feasibility AnalysisMicrogrid Institute's multidisciplinary team brings decades of experience in every facet of energy project development. On the foundation of this expertise, we provide objective and thorough analysis to support project planning, development, and execution. Our three-phase approach to feasibility assessment ensures that project factors and options are clearly understood by sponsors and stakeholders before they make strategic investment decisions.
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Phase I:
Pre-Feasibility Review Many key factors affecting the viability of a project can be readily identified in a pre-feasibility review. Using our Five-Factor Viability Matrix, our multi-disciplinary team considers 16 separate elements to yield an overall viability grade and quantitative viability scores along five factors – Economic, Technical, Legal, Market, and Process (plus extenuating or special factors). |
Phase II:
Technical Feasibility Analysis Any successful project depends on a solid foundation of operational design, technology, engineering, and system integration. Microgrid Institute leads in-depth analysis of microgrid project technical feasibility, applying world-class engineering and design capabilities. We take a multi-disciplinary and iterative approach, considering interdependent issues and refining project plans to address factors affecting project feasibility to support a successful project. |
Phase III:
Development Feasibility Study The difference between an economically successful development and a pure science project is usually found in regulatory, economic, and strategic factors. Microgrid Institute's team defines and analyzes key issues and produces strategic roadmaps to ensure successful project development. |
Five Factor Viability Methodology
Microgrid Institute supports project feasibility and development with a five-factor viability methodology. This multi-disciplinary approach addresses a variety of interdependent factors to identify development barriers and opportunities, and to yield integrated project plans that are ready for development and deployment. This methodology requires finding optimal answers to complex questions:
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