Behind-the-Meter Energy Storage Capacity Estimation
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Solution Overview
Problem
Utilities face challenges in accurately estimating the capacity and usage patterns of behind-the-meter energy storage and distributed energy generation units, leading to operational issues like voltage fluctuations and inadequate supply planning due to the lack of monitoring and inaccurate predictions.
Innovation Solution
A processor-implemented method and system that estimates the effective capacity and usage pattern of behind-the-meter energy storage by receiving data samples from utilities, determining yield from distributed energy generation units, estimating original energy demand, and calculating charging or discharging values to segregate charging and discharging schedules, thereby determining the effective capacity of energy storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If behind-the-meter energy storage and distributed energy generation units are deployed to meet consumer demand, then energy supply flexibility and renewable energy utilization are improved, but accurate estimation of storage capacity and usage patterns becomes difficult leading to voltage fluctuations and inadequate supply planning
Solution Approach 1:
The patent introduces an intermediary estimation system that uses observable manifestations (power flow patterns, energy exchange data) as mediators to infer hidden behind-the-meter storage capacity. This intermediary approach allows utilities to estimate storage characteristics without direct monitoring, resolving the contradiction between deploying hidden storage resources and maintaining measurement accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where estimated storage capacity and usage patterns are continuously refined based on observed power flow patterns and energy exchange data. This feedback loop improves estimation accuracy over time, allowing the system to maintain precise measurements even as storage deployment increases and creates more complex network patterns.
2Quantity of substance
If small-scale behind-the-meter energy storage units are deployed widely, then distributed energy utilization is improved, but monitoring and estimation capability of utilities deteriorates due to lack of direct metering
Solution Approach 1:
The patent enables the utility's estimation system to serve itself by using routinely collected power flow and energy exchange data to automatically infer storage capacity and usage patterns. This self-service approach eliminates the need for separate monitoring infrastructure, allowing widespread deployment of small-scale storage while maintaining estimation capability through automated analysis of existing data streams.
Solution Approach 2:
The patent makes the utility's existing measurement infrastructure universal by enabling it to serve dual purposes: traditional power flow monitoring and behind-the-meter storage estimation. By extracting multiple insights from the same data sources, the system can monitor both conventional and distributed energy resources without requiring additional specialized measurement devices.
3Reliability
If accurate prediction of energy storage capacity is required for adequate supply planning, then supply reliability is improved, but computational complexity and data processing requirements increase significantly
Solution Approach 1:
The patent applies partial action by focusing estimation efforts on the most critical parameters (storage capacity and usage patterns) rather than attempting to measure all possible characteristics. This selective approach achieves adequate supply planning reliability by concentrating computational resources on the parameters that most directly impact supply adequacy and voltage stability.
Solution Approach 2:
The patent performs preliminary estimation of storage capacity and usage patterns using available data before detailed supply planning is conducted. This preliminary action provides sufficient information for adequate supply planning without requiring complex real-time analysis, allowing planners to make informed decisions while avoiding excessive computational complexity during the planning process.
Data Source
AI summary
The present disclosure provides a method and a system for estimating capacity and usage pattern of behind-the-meter energy storage in electric networks. Conventional techniques on estimating an effective capacity of behind-the-meter energy storage of a consumer, in presence of distributed energy generation units is limited, computationally intensive and provide inaccurate prediction. The present disclosure provides an accurate estimate of the effective capacity and usage pattern of behind-the-meter energy storage of a target consumer utilizing data samples received from a utility in presence of one or more distributed energy generation units, using an energy balance equation with less computation and accurate prediction. Based on accurate estimation of the effective capacity and usage pattern, the utility may plan for proper infrastructure to meet power demands of the consumers.