Adaptive Load Aggregation for Emergency Frequency Support
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Solution Overview
Problem
Conventional frequency control methods, such as hierarchical control and under-frequency load shedding, are inadequate in responding to major disturbances and contingencies in power grids due to their lack of granularity and reliance on centralized communication networks, which can lead to severe frequency drops and blackouts.
Innovation Solution
A hybrid strategy combining centralized online contingency estimation and parameter setting at a cloud control center with decentralized real-time measurement and local decision-making by smart outlets, enabling adaptive and rapid frequency regulation through the aggregation of distributed loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If centralized frequency control methods are used, then coordination between devices is improved, but response speed deteriorates due to communication network delays
Solution Approach 1:
The control system is segmented into a centralized cloud control center for parameter setting and decentralized smart outlets for real-time decision making. This segmentation allows the centralized component to handle coordination while the decentralized component responds immediately to frequency disturbances without waiting for communication network commands.
Solution Approach 2:
The cloud control center pre-calculates and sends switching-off conditions to smart outlets in advance. When frequency disturbances occur, smart outlets can immediately execute pre-received commands without real-time communication delays, achieving both coordination and fast response.
2Reliability
If under-frequency load shedding schemes are used, then frequency stability is improved, but load shedding granularity deteriorates as entire areas are cut off
Solution Approach 1:
The load shedding control is segmented from area-level to outlet-level granularity. Individual smart outlets can independently control specific appliances, allowing selective load shedding of trivial loads while preserving critical loads within the same area, thus improving both frequency stability and operational precision.
Solution Approach 2:
Different smart outlets are assigned different switching-off conditions based on local load characteristics and importance. Critical loads receive protection while trivial loads are shed first, implementing differentiated quality control at local levels rather than uniform area-wide shedding.
3Speed
If distributed frequency control methods are used, then response speed is improved, but adaptability to power system state variations deteriorates
Solution Approach 1:
The cloud control center performs preliminary contingency estimation and calculates optimal switching-off conditions based on current power system state. These pre-calculated conditions are sent to smart outlets, enabling fast local response that is adapted to the actual system state without real-time communication delays.
Solution Approach 2:
The system implements feedback through continuous frequency measurement at smart outlets and periodic state estimation at the cloud control center. The control center updates switching-off conditions based on feedback about system state variations, ensuring adaptability while maintaining fast local response capability.
Data Source
AI summary
Systems and methods are disclosed for power management by estimating power contingency of a grid at a cloud control center; performing decentralized real-time measurement and making local decisions at one more computer controlled outlets connected to the grid; and aggregating distributed loads to provide emergency frequency support to the grid.