Distributed Power-System Project Discovery with Digital Twins
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Solution Overview
Problem
The high costs and complexities associated with assessing and obtaining approval for power-system projects, particularly in distributed systems, make it difficult to amortize overhead and secure funding, especially for projects under $2M, hindering the implementation of renewable energy solutions.
Innovation Solution
A computer system utilizing a pretrained neural network and digital twin to automate the planning, identification, and modification of power-system projects, incorporating data such as wind and solar data, land ownership, and regulatory information, to generate and optimize plans that reduce costs and increase approval chances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional project assessment methods are used for distributed power systems, then project approval can be obtained, but the overhead costs become too high to amortize for smaller projects
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing regulatory requirements, environmental data, and project parameters in a structured knowledge base before actual project assessment. This allows automated evaluation and plan generation without requiring full manual assessment for each project, thereby reducing overhead costs while maintaining approval reliability
Solution Approach 2:
The system creates simplified copies or representations of complex regulatory and environmental assessment processes through automated algorithms and digital twins. These computational models replicate the essential evaluation functions without requiring full-scale physical or manual assessments, reducing costs while preserving approval quality
2Productivity
If centralized power system projects are pursued, then economies of scale can be achieved, but project costs exceed $100M making them inaccessible to many utilities
Solution Approach 1:
The system enables segmentation of power systems into distributed smaller projects (e.g., individual wind turbines, solar installations) that can be assessed and approved independently. This allows utilities to pursue multiple smaller projects with lower individual costs rather than requiring single large centralized projects, improving accessibility while maintaining overall productivity through portfolio effects
3Device complexity
If distributed power system projects are pursued, then project costs are reduced and risks are lowered, but overhead amortization becomes difficult for projects under $2M
Solution Approach 1:
The system enables self-service by allowing automated generation of project plans, environmental assessments, and regulatory compliance documentation without requiring extensive external consulting or manual preparation. This reduces the overhead burden on small projects, making them economically viable while maintaining assessment quality and approval chances
Data Source
AI summary
A computer system (which may include one or more computers) that identifies a plan for a power-system project is described. During operation, the computer system may access stored information that specifies plans for power-system projects. Then, based at least in part on the information, the computer system may estimate risks and/or ROIs for the power-system projects. Moreover, based at least in part on the estimated risks and/or ROIs, the computer system may identify the plan for the power-system project in the plans for the power-system projects. Next, the computer system may provide second information specifying the identified plan for the power-system project.