Simulated sizing and siting of a plurality of new energy generation facilities to provide electricity for an industrial load

The system optimizes the placement and sizing of renewable energy facilities using probabilistic techniques to address the complexity of large-scale project development, ensuring efficient and cost-effective power distribution for industrial loads.

WO2026147793A1 Publication Date: 2026-07-09INVENTUS HOLDINGS LLC
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Patent Information

Application Number
PCT/US2025/061132
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-12-30
Filing Date
2025-12-23
Publication Date
2026-07-09

AI Technical Summary

Technical Problem

The development of large-scale renewable energy projects is complex and lengthy, often resulting in suboptimal site selection due to numerous variables and constraints, particularly for large industrial loads like data centers and hydrogen production facilities, which require an efficient mix of renewables, storage, and strategic placement to minimize grid strain and meet renewable energy goals.

Method used

A system and method using probabilistic techniques, such as simulated annealing, to optimize the spatial arrangement of new energy generation facilities by simulating the sizing and siting of multiple facilities, considering land parcel criteria, renewable resources, and transmission lines, while incorporating constraints to approximate the global minimum cost.

Benefits of technology

Facilitates efficient and cost-effective power distribution by identifying optimal locations and sizes for energy generation systems, ensuring compliance with regulatory constraints, and providing a visual interface for intuitive decision-making.

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Abstract

A system and method are provided for simulating the sizing and siting of energy generation facilities to supply electricity for a recommended industrial load. The method begins by accessing specific criteria for each land parcel in a portfolio and filtering out unviable parcels based on factors such as existing wind or solar installations, protected areas, or parcel size. An objective function is calculated to represent the overall cost of generating electricity to meet the load. The system executes multiple design simulations, generating random placements of energy facilities based on criteria like industrial load size and location, renewable energy resource availability, and transmission line proximity. For each simulation, the cost of construction and electricity delivery is calculated to identify the lowest possible cost. Using a probabilistic technique, the method approximates the global minimum cost and ranks each simulation by cost-efficiency, helping identify optimal land parcels for energy facility placement.
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