Energy Storage Siting Using Arbitrage Value Index
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Solution Overview
Problem
Existing methods for siting energy storage facilities in electrical grids are inefficient due to their centralized perspective, limited applicability to grids with thousands of nodes, and failure to consider a range of energy storage operational and technical factors, leading to suboptimal location and sizing of battery storage facilities.
Innovation Solution
An energy storage siting system that evaluates thousands of nodes across large electrical grids using an Arbitrage Value Index (AVI) to identify optimal locations for utility-scale battery energy storage facilities, considering technical and operational parameters, and generating detailed design parameters for charge/discharge patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a centralized perspective is used to site energy storage facilities, then the decision-making process is simplified, but the applicability to grids with thousands of nodes is limited and the results are suboptimal
Solution Approach 1:
The patent segments the energy storage siting problem into multiple independent components: (1) identifying candidate nodes based on grid constraints, (2) evaluating technical parameters for each candidate, (3) calculating economic metrics, and (4) ranking locations. This segmentation allows the system to handle thousands of nodes efficiently while maintaining comprehensive analysis capabilities.
2Ease of manufacture
If traditional siting methods are used, then the process is simpler, but the location and sizing of battery storage facilities are suboptimal, limiting performance and accelerating calendar life diminishment
Solution Approach 1:
The patent performs preliminary actions by systematically evaluating multiple technical parameters (duration, power rating, state of charge constraints, cycle-life) and economic metrics (LMP, arbitrage opportunities) before final site selection. This preliminary analysis ensures that selected locations optimize both performance and calendar life, avoiding suboptimal deployments.
Solution Approach 2:
The patent incorporates multiple technical parameters (storage duration, power rating, state of charge, cycle-life) and economic parameters (LMP, arbitrage value) into the siting decision framework. By analyzing how these parameters interact across different locations, the system identifies optimal sites that maximize facility performance and extend calendar life.
3Productivity
If technical parameters such as storage duration and power rating are not considered, then the siting process is faster, but the facility deployment is inefficient and calendar life is accelerated
Solution Approach 1:
The patent replaces traditional trial-and-error or rule-of-thumb siting approaches with a systematic computational framework that automatically evaluates technical parameters (duration, power rating, cycle-life) against grid conditions. This substitution enables comprehensive parameter analysis without significantly increasing process time, as the evaluation is performed through automated calculations rather than manual assessment.
Data Source
AI summary
Systems and methods for identifying optimal siting locations for an energy storage system. Siting locations are identified based on a value index derived from pricing data associated with a plurality of nodes on an electrical grid. An index is derived for each selected node of the plurality of nodes to produce a siting recommendation.