Electrochemical Energy Storage Intertemporal Management
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Solution Overview
Problem
Current methods for managing electrochemical energy storage (EES) degradation lack a comprehensive and rigorous approach to optimize life-cycle benefits across different decision horizons, leading to suboptimal operational decisions and inaccurate economic valuation.
Innovation Solution
An intertemporal decision framework that uses the marginal benefit of usage (MBU) metric to coordinate short-term, mid-term, and long-term EES scheduling, considering cycling and calendar degradation constraints, to maximize life-cycle efficiency and value, while also facilitating investment and subsidy decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If EES usage rate is increased to maximize short-term benefits, then short-term profit is improved, but EES functional lifetime is reduced due to higher degradation
Solution Approach 1:
The patent applies dynamics by making the operational parameters of EES adjustable and adaptable over time. The system dynamically optimizes charge/discharge schedules, state of charge limits, and cycling rates based on real-time conditions and forecasts. This allows the EES to operate at higher utilization rates when conditions are favorable while preserving capacity when degradation risks are high, thus resolving the contradiction between short-term productivity and long-term duration.
Solution Approach 2:
The patent employs preliminary action through day-ahead forecasting and pre-planned scheduling. By predicting future price signals, weather conditions, and EES state, the system prepares optimal operational schedules in advance. This allows operators to anticipate high-benefit opportunities and plan appropriate usage rates, balancing short-term profit maximization with long-term lifetime preservation through proactive rather than reactive decision-making.
2Duration of action of stationary object
If EES operation is limited to minimize degradation and wait for better opportunities, then EES lifetime is extended, but short-term profit is reduced due to underutilization
Solution Approach 1:
The system dynamically adjusts the balance between conservation and utilization based on real-time and forecasted conditions. Rather than static underutilization, the EES operates at optimized rates that respond to changing market prices, weather forecasts, and system state. This dynamic approach ensures the EES is utilized sufficiently to capture short-term benefits while avoiding excessive degradation, resolving the contradiction between lifetime extension and productivity.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring EES state (state of charge, state of health, temperature) and comparing actual performance against forecasts and targets. This feedback loop allows the system to learn from past operations and adjust future schedules to optimize both lifetime and short-term benefits, preventing both over-utilization and under-utilization scenarios.
3Ease of operation
If traditional generators' scheduling approach is applied to EES, then operational simplicity is maintained, but decision optimality is reduced due to ignoring degradation intertemporal requirements
Solution Approach 1:
The patent introduces an intermediary layer between simple operational commands and complex degradation management. The day-ahead optimization schedule acts as an intermediary that translates simple market price signals and operational constraints into sophisticated charge/discharge decisions that inherently account for degradation. This intermediary scheduling layer maintains ease of operation while achieving optimal decisions that traditional real-time control cannot provide.
Solution Approach 2:
By performing optimization calculations in advance (day-ahead), the system prepares detailed operational schedules that incorporate degradation considerations before actual operation begins. This preliminary action allows complex intertemporal optimization to be completed offline, with simple day-ahead schedules guiding real-time operations, thus maintaining operational simplicity while achieving decision optimality.
4Device complexity
If Levelized Cost of Degradation (LCOD) method is used to account for degradation cost, then degradation monetization is simplified, but decision accuracy is reduced due to sunk cost bias and time-invariant marginal cost
Solution Approach 1:
The patent changes the fundamental parameters used in degradation valuation. Instead of using fixed LCOD based on initial capital cost, the system employs dynamic marginal cost of degradation that varies with EES state (state of charge, state of health, temperature), operating conditions, and time. This parameter transformation allows degradation costs to reflect actual marginal impacts on lifetime, improving decision accuracy while maintaining computational tractability through day-ahead optimization.
Solution Approach 2:
The system performs preliminary calculation of marginal degradation costs as part of the day-ahead optimization process. By pre-computing these dynamic costs based on forecasted operations and current EES state, the system avoids the need for complex real-time degradation accounting during actual operation. This preliminary action embeds accurate degradation valuation into the scheduling process without adding operational complexity.
Data Source
AI summary
Methods and software for electrochemical energy storage management including operation, planning, and valuation. The decision objective for operation is to maximize the total/remaining life-cycle benefit of electrochemical energy storage, subject to degradation and other operational constraints. The operational decisions are both short term and long term, to address the intertemporal trade-offs brought by degradation issues. Two metrics are proposed for operational and planning decisions respectively: marginal benefit of usage and average benefit of usage. A sample algorithm is provided to solve the multi-timescale optimization problem.