Geo-Spatial Planning and Optimal Placement of Renewable Energy Systems

Sergey Malinchik


Energy investment strategies, renewable energy, wind power, resource allocation, energy planning, genetic algorithm


This paper describes an innovative concept and tool Geo-Spatial Planner for Energy Investment Strategies (GSPEIS) designed for large-region renewable energy planning and optimal development. The tool brings together three key components: (i) geo-spatial visualization framework that enables the user to explore and configure the problem space, (ii) simulation engine to approximate the investment and development scenarios, and (iii) optimization module based on genetic algorithm allowing to optimize across resources and infrastructure targeting different objectives such as investment return, energy production, and revenue. We demonstrate here by a few experiments that our approach with a heavy focus on user involvement enables to efficiently navigate and find optimal solutions within large search space while respecting diverse constraints and preferences.

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