Hierarchical Source-Network-Load-Storage Scheduling for Renewable Grid Balance
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Solution Overview
Problem
The existing electric power systems face issues of unreasonable distribution and inefficiency due to the lack of systematic optimization across power supplies, power grids, electricity consumption loads, and energy storage devices, particularly in contexts of renewable energy sources like wind and photovoltaics, leading to volatility and uncertainty.
Innovation Solution
A hierarchical and graded source-network-load-storage multi-subject collaborative scheduling method and system that integrates data from environment, power generation, and electricity consumption and storage devices to optimize energy distribution and balance energy supply and demand, utilizing data from environment, power data, and electricity generation, and storage devices to optimize energy distribution and balance energy supply and demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional independent operation of generation, transmission, distribution, and use is adopted, then system simplicity is maintained, but energy distribution reasonability and efficiency deteriorate
Solution Approach 1:
The system divides the electric power system into four independent but coordinated segments: generation, transmission, distribution, and use. Each segment operates semi-independently with its own scheduling module while being coordinated through hierarchical control, allowing optimized energy distribution without complete system redesign
Solution Approach 2:
The scheduling system implements a nested hierarchical structure with primary scheduling (generation level) and secondary scheduling (distribution and use levels). The primary scheduling module coordinates with secondary modules, creating a nested control architecture that improves efficiency while maintaining manageable complexity
2Reliability
If renewable energy sources like wind and photovoltaics are integrated, then energy sustainability is improved, but volatility and uncertainty increase
Solution Approach 1:
The system performs preliminary scheduling of renewable energy sources based on predicted generation patterns. By pre-scheduling generation, transmission, distribution, and use in sequence, the system prepares for volatility before it occurs, smoothing out fluctuations and improving supply stability
Solution Approach 2:
The scheduling system incorporates feedback mechanisms that continuously monitor actual renewable energy generation and consumption. This feedback allows dynamic adjustment of scheduling decisions to adapt to volatility and uncertainty in renewable energy sources
3Productivity
If multi-source coordination and multi-level energy management are implemented, then energy optimization is improved, but scheduling complexity increases
Solution Approach 1:
The scheduling system is segmented into distinct modules: primary scheduling module for generation, secondary scheduling modules for distribution and use at different levels. This segmentation allows complex multi-source coordination to be managed through standardized, modular interfaces
Solution Approach 2:
The system adds a hierarchical dimension to scheduling, organizing control from primary (generation-level) to secondary (distribution and use-level) levels. This dimensional approach transforms complex multi-source coordination into a structured multi-level management process
Data Source
AI summary
The present invention discloses a hierarchical and graded source-network-load-storage multi-subject collaborative scheduling method and system, and relates to the technical field of new energy. The method includes: obtaining power supply data, obtaining electricity consumption data corresponding to each level of an urban area, and obtaining energy storage data of electricity storage devices; obtaining historical data sets, and analyzing the power supply data, the electricity consumption data, and the energy storage data to obtain estimated electric energy data; and calling the electricity storage devices in surrounding regions according to the adjusted secondary electricity consumption data of the urban area. The present invention may optimize and schedule on sources, networks, loads, and storage.