Power Storage Control Using Dual Prediction Models
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Solution Overview
Problem
Existing power management systems struggle to rapidly control charging and discharging of power storage apparatuses to mitigate steep changes in consumed power, leading to increased electricity costs and degraded power quality due to peak demand and generation fluctuations.
Innovation Solution
A control apparatus with predictors and a controller that uses both long-term and short-term prediction models to manage charging and discharging of power storage apparatuses, setting charging or discharging power at different intervals based on predicted power changes, ensuring optimal energy balance and reducing steep changes in received power from the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the power storage apparatus charges or discharges rapidly to respond to steep changes in consumed power, then the response speed improves, but the charged electric energy may reach the lower limit prematurely, requiring advance charging that increases received power from the network
Solution Approach 1:
The control apparatus performs advance charging of the power storage apparatus when predicted future discharging will cause the charged electric energy to reach the lower limit. This preliminary action ensures that sufficient energy is available for future discharging operations while managing the received power from the network in advance.
Solution Approach 2:
The system dynamically adjusts charging and discharging operations based on real-time monitoring of charged electric energy levels and predicted future demands. The control apparatus flexibly modifies the charging/discharging rates to maintain optimal energy levels while responding to power network conditions.
2Device complexity
If the control apparatus uses only long-term prediction models with longer time intervals, then the overall power management is simplified, but it cannot rapidly control charging and discharging to mitigate steep changes in consumed power
Solution Approach 1:
The control apparatus segments the prediction and control process into two distinct time intervals: a first time interval using a first prediction model for overall power management, and a second time interval using a second prediction model for rapid response to steep changes. This segmentation allows the system to handle both long-term planning and short-term emergencies effectively.
Solution Approach 2:
The system applies partial control actions at different time scales - using the first prediction model for general power management and the second prediction model specifically for addressing steep changes in consumed power. This partial application of different control strategies optimizes both simplicity and responsiveness.
3Loss of energy
If the power storage apparatus discharges to reduce peak received power from the network, then electricity costs are reduced, but the charged electric energy decreases and may reach the lower limit
Solution Approach 1:
The control apparatus performs advance charging when predicted future discharging operations will cause the charged electric energy to reach the lower limit. This ensures that the power storage apparatus has sufficient energy reserves to continue discharging for peak shaving purposes without risking energy depletion.
Solution Approach 2:
The system continuously monitors the charged electric energy levels and uses this feedback to adjust charging and discharging operations. When the charged electric energy approaches the lower limit, the control apparatus modifies discharging rates or increases charging to maintain energy reserves while still achieving cost reduction through strategic discharging.
Data Source
AI summary
A long-term predictor predicts long-term predicted power indicating temporal changes in consumed power of a customer using a long-term prediction model. A short-term predictor predicts short-term predicted power indicating temporal changes in the consumed power of the customer immediately after a current time, using a short-term prediction model, based on temporal changes in the consumed power of the customer immediately before the current time. A controller controls charging and discharging of a power storage apparatus at intervals based on the long-term predicted power and the short-term predicted power. The controller predicts temporal changes in charging power, discharging power, and charged electric energy of the power storage apparatus, and when the charged electric energy is predicted to reaches a lower limit due to discharging of the power storage apparatus, the controller charges power from the power network to the power storage apparatus in advance.