Energy Storage System Dynamic Charging Control
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Solution Overview
Problem
Existing energy storage systems (ESS) do not operate with optimum efficiency and often have unnecessarily oversized dimensions, leading to inefficiencies and increased costs due to sudden imbalances between generation and consumption in electric power systems, particularly with renewable energy variations.
Innovation Solution
A method and system for dynamically adjusting the charging/discharging rate of an ESS based on measured state of charge and a time-dependent forecast vector of power system properties, using a control unit to optimize operational efficiency and reduce storage capacity requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ESS operates with fixed charging/discharging rates, then system simplicity is maintained, but operational efficiency is suboptimal
Solution Approach 1:
The patent implements dynamic charging/discharging rates that adapt to real-time power system conditions. The control system continuously monitors frequency deviations and adjusts the ESS operating point along its discharge curve, transitioning from static to dynamic operation to maximize efficiency while maintaining manageable complexity through automated control algorithms.
Solution Approach 2:
The patent changes the operating parameters of the ESS by utilizing different portions of the discharge curve based on system needs. By varying the discharge rate and state-of-charge levels dynamically, the system optimizes efficiency without requiring complex hardware modifications, achieving improved productivity through parameter optimization.
2Reliability
If ESS has larger storage capacity, then frequency regulation capability is improved, but system dimensions and costs increase
Solution Approach 1:
The patent applies partial action by utilizing only the optimal portion of the ESS discharge curve for frequency regulation. Instead of requiring the entire storage capacity to be available at all times, the system dynamically accesses only the necessary energy levels, reducing the required total storage capacity while maintaining adequate frequency regulation capability.
Solution Approach 2:
The control system performs preliminary optimization by pre-determining the optimal operating points on the discharge curve based on forecasted power system conditions. This allows the ESS to be sized more efficiently, as the system proactively prepares optimal charge/discharge schedules rather than requiring excessive capacity to handle all contingencies.
3Productivity
If ESS operates without time-dependent forecasting, then system complexity is reduced, but operational optimization is limited
Solution Approach 1:
The patent implements feedback control by continuously monitoring actual power system frequency and comparing it with forecasted values. The control system uses this feedback to adjust the ESS charging/discharging rates in real-time, optimizing operational efficiency while managing complexity through closed-loop control that automatically adapts to deviations from forecasts.
Solution Approach 2:
The system performs preliminary forecasting of power system conditions to pre-determine optimal ESS operating schedules. By anticipating future system states and preparing optimal charge/discharge plans in advance, the system achieves operational efficiency improvements without requiring complex real-time adjustments, reducing the burden on the control system.
Data Source
AI summary
The present disclosure is concerned with operation of an energy storage system (ESS) connectable to an electric power system. The charging-discharging schedule of the ESS can be determined through application of a time-dependent forecast of ESS and power system states based on historical data. Exemplary embodiments can include ESSs which have been historically activated with a certain periodicity, for example, for power system load leveling, frequency regulation, arbitrage, peak load shaving and/or integration of renewable power generation.