Clean Energy Factor for Power Grid Congestion Management
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Solution Overview
Problem
Current energy analytics systems are unable to accurately describe and manage local congestion and losses in electric power grids, leading to inefficiencies and increased costs, especially in systems with abundant wind and solar power, as they rely on emissions data which is inaccurate and secondary to other costs like congestion and losses.
Innovation Solution
The introduction of a clean energy factor, calculated using wind number and solar boost values, which represents locational variations in congestion and losses independently of emissions, allowing for more accurate energy management and load switching, reducing energy costs and the need for distribution system investments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If emissions data is used to manage energy consumption, then emissions can be reduced, but accuracy in describing local congestion and losses deteriorates
Solution Approach 1:
The patent extracts the inaccurate emissions-based metric from the energy management system and replaces it with a clean energy factor that directly measures congestion and losses. This separation allows the system to focus on the actual problem (congestion and losses) rather than being misled by proxy data (emissions).
Solution Approach 2:
The patent changes the fundamental parameter used for energy management from emissions data to a clean energy factor. This parameter change fundamentally alters how the system measures and manages energy consumption, replacing an inaccurate proxy with a direct measurement of the actual problem.
2Ease of operation
If regional emissions signals are used to switch loads, then emissions management is simplified, but local congestion and loss costs increase
Solution Approach 1:
The patent applies local quality by creating a clean energy factor specific to each location and time period, capturing local variations in congestion and losses. This allows load switching decisions to be made based on local conditions rather than regional averages, optimizing energy management at the most appropriate granularity level.
Solution Approach 2:
The clean energy factor serves as an intermediary metric that translates complex local congestion and loss data into a usable form for load switching decisions. It mediates between the complexity of actual grid conditions and the simplicity needed for consumer-facing energy management.
3Reliability
If fossil-fuel burning plants are used to balance peak demand, then reliable power supply is maintained, but operational costs increase
Solution Approach 1:
The patent enables preliminary action by using clean energy factor data to shift loads to periods when congestion and losses are lower. By proactively managing demand based on predicted grid conditions, the system can avoid expensive peak-demand periods without compromising reliability, instead of reacting to peak conditions after they occur.
Data Source
AI summary
The disclosed technology relates to methods, energy analysis computing devices, and non-transitory computer readable media for reducing local congestion and loss in electric power grids. In some examples, the technology obtains energy generation and wholesale price data from a balancing authority server. The energy generation data comprises wind generation, solar power generation, and thermal power resource data. A wind number value is generated, based on the wind generation and thermal power resource data, a solar boost value is generated, based on the solar power generation and thermal power resource data, and a regional clean energy factor value is generated based on the wind number and solar boost values. A local clean energy factor value is generated based on the regional clean energy factor value and the wholesale price data. A notification is sent to a user device when the local clean energy factor exceeds a threshold.