Decentralized Grid Control via Pricing Signals
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Solution Overview
Problem
Current electrical grids face challenges in managing the flow of electricity from renewable sources due to their inherent unreliability, leading to difficulties in balancing supply and demand while preserving privacy constraints among energy operators.
Innovation Solution
A decentralized optimization method that allows energy operators to determine their own electricity needs independently, using sensitivities to variations in energy requests to balance supply and demand through semismooth equations and Newton-based methods, ensuring privacy preservation and faster convergence rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a decentralized optimization method is used to preserve privacy constraints among energy operators, then privacy preservation is improved, but the complexity of balancing supply and demand increases
Solution Approach 1:
The patent segments the centralized optimization problem into multiple independent local optimization problems, one for each energy operator. Each operator independently determines their electricity needs without sharing sensitive information, while a coordinator balances the overall supply and demand using aggregated data. This segmentation preserves privacy while distributing the computational complexity across multiple entities.
Solution Approach 2:
The patent introduces a coordinator as an intermediary entity that receives aggregated demand and supply information from energy operators without accessing their private data. The coordinator solves the global balancing problem using this aggregated information and sends back pricing signals to operators. This intermediary structure enables centralized coordination while maintaining decentralized privacy preservation.
2Reliability
If traditional optimization methods are used to balance supply and demand, then convergence is achieved, but the convergence rate is slow
Solution Approach 1:
The patent changes the optimization parameters by introducing pricing signals as dynamic variables that guide energy operators' decisions. Instead of directly optimizing power flow, the system optimizes prices that indirectly control operator behavior. This parameter transformation enables faster convergence by creating a more responsive feedback mechanism between supply, demand, and pricing.
Solution Approach 2:
The patent implements a feedback mechanism where the coordinator sends pricing signals to energy operators based on the current balance between supply and demand. Operators adjust their electricity requests based on these prices, which in turn affects the overall balance. This closed-loop feedback system accelerates convergence by continuously guiding the system toward equilibrium through price adjustments.
3Adaptability or versatility
If renewable energy sources are integrated into the electrical grid, then green energy usage increases, but the unreliability of supply increases
Solution Approach 1:
The patent applies dynamics by making the pricing signals and optimization parameters adaptive rather than static. The system continuously adjusts prices based on real-time supply and demand conditions, allowing it to respond to the variable nature of renewable energy generation. This dynamic approach enables the grid to accommodate unreliable renewable sources while maintaining overall reliability through flexible price-based coordination.
Solution Approach 2:
The patent changes the operational parameters of the electrical grid by introducing price as a controllable variable that responds to renewable energy availability. When renewable generation is high, prices decrease, encouraging increased consumption. When generation is low, prices increase, reducing demand. This parameter change enables the system to adapt to renewable variability while maintaining supply-demand balance.
Data Source
AI summary
An amount of electricity passing through an electrical grid is controlled by balancing amount of electricity for each energy provider and each energy consumer. In response to transmitting requests for the electricity, a decentralized control system receives an amount of electricity each energy operator agrees to supply or demand to satisfy the requests, as well as a sensitivity of the amount of electricity to a variation of at least one parameter of a corresponding request. The system updates parameters of at least some requests in directions governed by the corresponding sensitivities to produce a balanced amount of electricity for each energy provider and each energy consumer. The system causes the energy providers to supply into the electrical grid their corresponding balanced amounts of electricity and causes the energy consumers to consume from the electrical grid their corresponding balanced amounts of electricity.