Load Management for Renewable Energy Apportioning Power to Consumers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for optimizing the chronological development of electric power consumption in local grids with wind or solar power generators often result in excessive reliance on public power grids, leading to inefficiencies and increased costs due to mismatched supply and demand patterns.
Innovation Solution
A method and apparatus that measure and manage electric power consumption at high temporal resolutions, apportioning power to individual consumers based on characteristic time curves and future supply prognoses to maximize local usage of renewable energy and minimize public grid utilization, using advanced control systems and data-driven strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If electric power from wind or solar generators is supplied to the public power grid when production exceeds local consumption, then excess electric power can be utilized, but the output power of the generators has to be curtailed when supply coincides with grid surplus, leading to loss of available electric power
Solution Approach 1:
The system performs preliminary actions by storing prognoses of electric power supply and characteristic time curves of consumption before the actual supply occurs. This allows the load management to pre-plan the apportionment of electric power to consumers, ensuring that power is allocated optimally when it becomes available, thereby preventing curtailment and energy loss.
Solution Approach 2:
The system dynamically adapts the apportionment of electric power based on real-time supply conditions and characteristic time curves of consumer demand. The load management continuously adjusts power distribution to match the chronological developing of supply and demand, enabling flexible response to varying generation levels and preventing both curtailment and grid dependency.
2Productivity
If electric power is apportioned to individual consumers based on high temporal resolution measurements and prognoses, then local consumption of renewable energy is maximized, but the complexity of the control system increases
Solution Approach 1:
The system segments the approach by measuring and analyzing the consumption characteristics of individual consumers separately. Each consumer's characteristic time curve is determined independently, allowing the load management to allocate power to specific consumers based on their unique patterns and the available supply, thereby optimizing local utilization without requiring a monolithic complex control system.
Solution Approach 2:
The system uses feedback from measured consumption data and supply conditions to continuously refine power apportionment decisions. By monitoring actual consumption against characteristic time curves and adjusting allocations accordingly, the system achieves high local energy utilization while maintaining manageable control complexity through data-driven adaptive management.
3Reliability
If the public power grid serves as a buffer for electric power to balance supply and demand, then energy security is maintained, but considerable costs are incurred that require compensation from grid operators
Solution Approach 1:
The system enables the local power grid to serve itself by autonomously balancing supply and demand through intelligent load management. By apportioning power based on prognoses and characteristic time curves, the system reduces dependency on the public grid as a buffer, thereby maintaining energy security while minimizing the costs associated with grid buffer services.
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
For optimizing a chronological developing of consumption of electric power by a group of different consumers (2 to 7) with regard to a supply of electric power including electric power from at least one wind or solar power generator (8), a consumption of electric power by the individual consumers (2 to 7) is measured to determine characteristic time curves of the consumption of electric power by the individual consumers (2 to 7); a prognosis of a chronological developing of the supply of electric power from the at least one power generator (8) is made for a future period of time; a plan for apportioning electric power to the individual consumers (2 to 7) within the future period of time is made based on the characteristic time curves of the consumption of electric power by the individual consumers (2 to 7) and adapted to the prognosis; and electric power is apportioned to the individual consumers (2 to 7) according to the plan within the future period of time. Apportioning electric power to the individual consumers (2 to 7) is executed via at least one switchable single connector for a single one of the individual consumers (2 to 7) and/or effected by accessing an interface of a controller (27) of at least one individual consumer (2 to 7).