Microgrid Power Targeting for Energy Storage Constraint Control
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Solution Overview
Problem
Microgrids connected to power systems face inefficiencies in energy management, particularly in optimizing energy use efficiency and minimizing the use-restricted periods of energy storage apparatuses, which affects overall energy savings and flexibility in demand response.
Innovation Solution
An energy management device that calculates a target value for received power in a microgrid based on supply and demand predictions, using objective functions that evaluate energy storage usage and electricity rates, with constraints on power limits to optimize energy efficiency and reduce arithmetic calculations, thereby minimizing the influence on the power system and maintaining electricity quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional energy management methods are used in microgrids, then the system operates with basic power control, but energy use efficiency is not optimized and use-restricted periods of energy storage increase
Solution Approach 1:
The energy management device performs supply and demand prediction in advance to calculate target received power values before actual power flow occurs. This preliminary calculation allows the microgrid to proactively optimize energy storage usage and minimize use-restricted periods, rather than reacting to power imbalances after they occur.
Solution Approach 2:
The system dynamically adjusts the target received power based on real-time supply and demand predictions, energy storage state, and varying electricity rates. This dynamic optimization continuously minimizes use-restricted periods while maximizing energy use efficiency, adapting to changing conditions rather than operating on fixed parameters.
2Productivity
If complex optimization algorithms are used to maximize energy efficiency, then energy use efficiency improves, but arithmetic calculation complexity increases
Solution Approach 1:
The patent extracts and applies only the essential constraints needed for optimization: upper and lower limits of received power and upper and lower limits of energy storage output power. By focusing on these critical constraints rather than attempting to optimize all possible parameters, the system achieves effective energy efficiency improvement with manageable calculation complexity.
Solution Approach 2:
The system changes the optimization approach by working with power limit parameters and predicted supply-demand values rather than attempting to optimize every operational parameter simultaneously. This parameter-focused approach simplifies the arithmetic calculations while still achieving meaningful energy efficiency improvements through targeted optimization.
3Loss of energy
If aggressive power control is implemented to optimize energy efficiency, then energy savings increase, but influence on the power system increases and electricity quality may deteriorate
Solution Approach 1:
The system applies preliminary anti-action by setting the target received power within predetermined upper and lower limits before power flow occurs. This prevents excessive power adjustments that could destabilize the connected power system, while still achieving energy savings through optimized energy storage management within safe operational boundaries.
Solution Approach 2:
The energy management device continuously monitors actual power flow against target values and adjusts operations to maintain electricity quality. This feedback mechanism ensures that energy optimization efforts do not push the system beyond stable operating conditions, balancing energy savings with power system stability and quality requirements.
Data Source
AI summary
An energy management device 50 for a microgrid S1 that is interconnected to a power system 1 and includes an energy storage apparatus 15. The energy management device 50 calculates a target value of received power of the microgrid, the target value of the received power optimizing energy use efficiency of the microgrid S1, based on a supply and demand prediction of power in the microgrid S1 with upper and lower limits of received power of the microgrid S1 and upper and lower limits of output power of the energy storage apparatus 15 as constraint conditions.