Predictive Energy Storage Control for Renewable Surplus and Deficit
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Solution Overview
Problem
Existing electrical energy storage systems (EESSs) fail to efficiently manage variable renewable energy sources, leading to suboptimal use of renewable energy and increased grid energy imports, resulting in inefficiencies and higher costs.
Innovation Solution
An EESS with a control unit that communicates with the inverter, retrieves data from external sources, and assesses energy output, storage, and usage to predict daily energy needs, directing the inverter to store surplus energy or import/export energy from the grid as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If known systems manage energy charging and discharging cycles without external data integration, then system operation is simple, but renewable energy utilization is suboptimal and grid imports increase
Solution Approach 1:
The control unit serves as an intermediary component that bridges the inverter and external data sources (weather forecasts, energy prices). It retrieves, processes, and acts on external information to optimize energy management decisions, thereby improving renewable energy utilization without requiring complex integration of multiple external systems directly into the inverter
Solution Approach 2:
The control unit implements feedback mechanisms by continuously monitoring system performance (energy generation, storage state, consumption patterns) and adjusting charging/discharging cycles based on predicted weather conditions and energy prices. This closed-loop control optimizes renewable energy utilization while maintaining manageable system complexity through automated decision-making
2Productivity
If energy is imported from the grid without predictive control, then energy supply is reliable, but costs increase due to variable tariffs
Solution Approach 1:
The control unit performs preliminary actions by predicting future energy generation based on weather forecasts and pre-charging the battery when energy prices are low or generation is expected to be high. This proactive approach reduces the need to import expensive energy during peak tariff periods while ensuring energy availability when needed
Solution Approach 2:
The system dynamically changes operational parameters (charging rate, discharge rate, grid import/export levels) based on varying conditions such as weather predictions and energy prices. This flexibility allows the system to optimize cost efficiency by importing energy during low-tariff periods and reducing imports during high-tariff periods while maintaining supply reliability
Data Source
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AI summary
An electrical energy storage system is provided characterised in that the system further comprises a control that retrieves information from one or more external data sources; the control unit receives information from the inverter in respect of output of the renewable energy source, the state of charge of the replenishable energy store, and energy usage; the control unit assesses the received information; the control unit determines whether the predicted daily output of the renewable energy source and the state of charge of the replenishable energy store is sufficient to meet the predicted daily energy usage; and the control unit directs the inverter: if there is a predicted surplus, to store surplus energy in the replenishable energy store and/or export energy to the grid; and if there is a predicted deficit, to import energy from the replenishable energy store and/or the grid. Also provided are a control unit for an electrical energy storage system, and methods of optimising energy efficiency in an electrical energy storage system or maximising return from an electrical energy storage system.