Hybrid Wind Power Forecasting and Battery Life Optimization
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Solution Overview
Problem
Hybrid wind power systems face challenges in maintaining consistent power output due to uncontrollable wind variations, leading to inefficient battery usage and increased battery replacement frequencies, which elevates operational costs.
Innovation Solution
A method and system that acquire actual wind power data, determine forecasted wind farm power estimates using multiple schemes, compute difference values, identify the best forecast scheme, and adjust battery set points to balance grid penalties while optimizing energy storage unit life, thereby regulating wind turbines and batteries based on subsequent forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a simple feedback based control algorithm is employed for smoothing power generated by the wind turbine, then power smoothing is achieved, but the battery is operated at a saturated level causing undesirable and large cycling which affects battery life
Solution Approach 1:
The patent changes the control parameters from simple feedback control to a model predictive control approach that uses a battery equivalent circuit model and considers state of charge constraints. This transforms the control strategy to optimize battery operating points and minimize cycling while maintaining power smoothing, thereby extending battery life without sacrificing stability
Solution Approach 2:
The patent performs preliminary action by using forecasted wind power data to predict future battery state of charge and cycling patterns before actual operation. This allows the control system to pre-optimize battery usage strategies, avoiding saturated operation and excessive cycling that would otherwise occur with reactive feedback control
2Reliability
If the battery is used to compensate for power variations in wind farms, then the required power to the grid is maintained, but the operational cost increases due to frequent battery replacement
Solution Approach 1:
The patent changes operational parameters by implementing state of charge constraints and optimized charge-discharge cycles based on forecasted wind power. This reduces unnecessary battery cycling and extends battery lifespan, thereby maintaining reliable power supply to the grid while significantly reducing operational costs associated with frequent battery replacement
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors actual wind power data against forecasted values and adjusts battery operation accordingly. This closed-loop control optimizes battery usage in real-time, preventing over-cycling and extending battery life, which reduces replacement frequency and operational costs while maintaining grid power stability
Data Source
AI summary
A method for optimizing a hybrid wind system including a wind farm having a plurality of wind turbines and one or more energy storage units, is presented. The method includes acquiring actual wind power data associated with one or more dispatch windows. The method includes determining forecasted wind farm power estimates corresponding to the dispatch windows using a plurality of forecast schemes. The method includes computing difference values by comparing the forecasted wind farm power estimates to the actual wind power data. The method includes identifying a wind power forecast scheme based at least in part on the computed difference values and balancing a penalty to the grid with life consumption of the energy storage units while regulating the wind turbines and the energy storage units based at least in part on a subsequent forecasted wind farm power estimate generated using the identified wind power forecast scheme.