Microgrid Energy Management System for Optimizing Storage Plans
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Solution Overview
Problem
Existing energy management systems for microgrids face challenges in rapidly changing weather conditions, leading to high calculation times and difficulties in updating charging/discharging plans for energy storage devices, which results in suboptimal response to changing electricity demand and renewable energy generation.
Innovation Solution
An energy management system that includes a prediction unit for forecasting electricity demand and renewable energy generation at fixed time intervals, and an optimization unit that derives an optimal charging/discharging plan for energy storage devices, considering uncertainty in predictions, thereby reducing calculation time and ensuring compliance with restricting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a simulation is performed whenever a case of prediction deviation occurs to evaluate operation costs, then the operation plan can minimize the weighted sum of operation costs of each case, but an enormous calculation time is required
Solution Approach 1:
The patent pre-calculates and stores operation costs for various prediction deviation cases in a lookup table before real-time operation. When prediction deviation occurs, the system directly retrieves pre-computed costs from the table rather than performing simulations, thereby maintaining optimization reliability while dramatically reducing calculation time to instantaneous access levels.
Solution Approach 2:
The patent computes and stores operation costs for a comprehensive set of prediction deviation cases in advance, covering more scenarios than may occur in practice. This excessive pre-computation ensures that any actual prediction deviation can be matched with pre-calculated optimal costs, eliminating the need for real-time simulation while guaranteeing cost optimization.
2Adaptability or versatility
If the operation plan for the energy storage device is frequently modified on a day when the weather often changes, then the system can respond to changing conditions, but performing a simulation each time may fail to keep up with the rate of change in weather
Solution Approach 1:
The patent pre-computes operation costs for multiple prediction deviation cases and stores them in a lookup table before weather changes occur. When weather conditions change and prediction deviation is detected, the system immediately retrieves the corresponding pre-computed costs and updates the operation plan without performing time-consuming simulations, thus keeping up with rapid weather changes.
Solution Approach 2:
The patent implements a dynamic operation plan update mechanism that uses real-time prediction deviation detection to select from pre-computed cost scenarios. The system dynamically adapts to weather changes by switching between pre-calculated operation plans based on current conditions, enabling rapid response without recalculation delays.
3Reliability
If accurate prediction of electricity demand and amount of renewable energy generation is attempted, then the charging/discharging plan can minimize operation costs, but the inherent difficulty and uncertainty in prediction make this challenging
Solution Approach 1:
The patent compensates for prediction uncertainty by pre-calculating operation costs for multiple prediction deviation cases (including both under-prediction and over-prediction scenarios). This beforehand cushioning approach ensures that even if predictions deviate from actual values, the system has pre-prepared cost information for corrected operation plans, maintaining reliability without requiring complex real-time prediction mechanisms.
Solution Approach 2:
The patent handles prediction uncertainty by changing the parameter approach from attempting highly accurate real-time prediction to using a set of predefined prediction deviation cases with associated costs. The system accepts a range of possible prediction outcomes and prepares corresponding operation plans in advance, simplifying the prediction system while maintaining operational reliability.
Data Source
AI summary
The energy management system is an energy management system for a microgrid including at least either one of an electrical load and a renewable energy power-generation system, and an energy storage device, the energy management system including: a prediction unit that predicts, at a fixed time interval, at least either one of an electricity demand and an amount of electricity generated from renewable energy, and an electricity fee, within a predetermined period; and an optimization unit that performs optimization for an optimum charging/discharging plan for the energy storage device by using a prediction result from the prediction unit and in consideration of uncertainty in prediction.