Distributed Ledger Control for Aggregated Power Grid Energy Resources
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Solution Overview
Problem
The integration of renewable energy sources into power grids faces challenges due to their volatility, requiring advanced load-side control systems to manage uncertainties and ensure demand response balance, which existing technologies struggle to address effectively.
Innovation Solution
A distributed optimization approach using secure, distributed transaction ledgers, such as blockchain technology, where DER controllers share condensed datasets to calculate global quantities, iteratively converging to optimal control actions that balance power consumption and satisfy local constraints, enabling efficient tracking of commanded power profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If renewable energy sources are integrated into power grids to meet demand, then energy sustainability and environmental benefits are improved, but system stability and reliability deteriorate due to volatility and forecasting uncertainties
Solution Approach 1:
The patent segments the power grid control into distributed energy resource controllers that operate independently at local levels while contributing to global optimization. Each DER controller manages local resources (solar, wind, storage) autonomously, reducing the impact of local volatility on overall grid stability while maintaining renewable integration.
Solution Approach 2:
The patent implements iterative feedback mechanisms where DER controllers exchange information about local conditions and control actions. The system continuously monitors renewable generation output, load demands, and control actions, then adjusts control strategies in subsequent iterations to maintain reliability despite renewable volatility.
2Productivity
If load-side control is implemented to optimize collective power consumption and accommodate renewable uncertainties, then demand response balance is improved, but system complexity increases due to coordination requirements
Solution Approach 1:
The control system is segmented into independent DER controllers that each optimize local load-side control actions. This distributed architecture reduces coordination complexity compared to centralized control, as each controller operates autonomously based on local conditions while contributing to overall demand response balance.
Solution Approach 2:
Each DER controller performs self-service by autonomously determining optimal control actions for its local resources based on received global information (Lagrange multipliers). The controllers independently adjust load-side consumption without requiring complex inter-controller coordination, simplifying the overall system architecture.
3Measurement precision
If distributed controllers share data iteratively to converge on optimal control actions, then solution accuracy is improved, but computational time and communication overhead increase
Solution Approach 1:
The patent extracts only the essential global information (Lagrange multipliers representing power balance constraints) that DER controllers need to make optimal decisions. By sharing only these condensed data elements rather than complete system states, the patent reduces communication overhead and iteration time while maintaining solution accuracy.
Solution Approach 2:
The patent transforms the complex multi-variable optimization problem into a simpler form by using Lagrange multipliers as key parameters. This parameter transformation allows controllers to converge on optimal solutions more quickly by focusing iterations on adjusting these critical parameters rather than all individual control variables.
Data Source
AI summary
Some embodiments may provide a distributed optimization technology for the control of aggregation of distributed flexibility resource nodes (e.g., associated with distributed energy resources) that operates iteratively until a commanded power profile is produced by aggregated loads. Some embodiments use a distributed iterative solution in which each node solves a local optimization problem with local constraints and states, while using global qualities (e.g., associated with a Lagrange multiplier) that are based upon information from each other node. The global qualities may be determined via a secure, distributed transaction ledger (e.g., associated with blockchain) using DER-specific information obtained in a condensed form (e.g., a scalar or vector) from each node at each iteration. The global qualities may be broadcast to the nodes for each new iteration. Embodiments may provide an iterative, distributed solution to the network optimization problem of aggregated load power tracking.