Distributed Ledger Energy Scheduling for Unit Commitment Coordination
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Solution Overview
Problem
The unit commitment problem in electrical power production is challenging due to the difficulty in coordinating a large number of generators and consumers with varying efficiencies and constraints, leading to inefficiencies, increased reserve requirements, and potential environmental and financial penalties.
Innovation Solution
A method and system utilizing a distributed ledger and smart contracts to enable improved energy forecasts and schedule corrections by independent computing means (workers) that propose adjustments to energy flow schedules, leveraging historical and external data, and receive automated feedback and compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central entity governs scheduling and trading of energy, then coordination of energy flow is achieved, but system complexity and computational requirements increase significantly
Solution Approach 1:
The patent segments the centralized scheduling function into distributed autonomous agents that operate independently at different levels of the energy system. Each agent manages local scheduling decisions, eliminating the need for a single complex central entity while maintaining coordination through standardized communication protocols and market mechanisms.
Solution Approach 2:
The patent introduces smart contracts as intermediary mechanisms that facilitate coordination between distributed agents without requiring direct complex interactions. These self-executing contracts encode scheduling rules and market transactions, acting as mediators that simplify agent-to-agent communication while ensuring reliable coordination.
2Reliability
If unit commitment problem is solved with many iterations and market participants, then production coordination is improved, but time consumption and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-defining scheduling rules, constraints, and market mechanisms in smart contracts before actual scheduling events occur. This allows the system to execute scheduling decisions rapidly by simply evaluating pre-programmed logic against current conditions, rather than performing complex iterative optimization in real-time.
Solution Approach 2:
The patent enables self-service through autonomous agents that independently make scheduling decisions based on pre-defined rules and market signals. Each agent autonomously determines its production schedule without requiring iterative coordination with a central entity, significantly reducing computational time while maintaining coordination quality.
3Measurement precision
If precise energy forecasts are generated under multiple constraints, then scheduling accuracy is improved, but computational resources and expertise requirements increase
Solution Approach 1:
The patent applies local quality by allowing different forecasting methods and constraint sets to be applied at different locations and time scales. Local agents use simplified forecasting appropriate to their specific context, while more complex centralized forecasting is applied only where necessary, reducing overall computational complexity while maintaining precision where it matters most.
Data Source
AI summary
A method for adjusting electrical energy flow schedules of a utility handling a plurality of distributed energy resources. The method comprising the steps of providing information regarding energy flow of the energy resources and storing said information on a distributed ledger; transferring energy schedules from the utility to the distributed ledger; transferring said information regarding the energy flow and the energy schedules from the distributed ledger to a computing means and computing proposed corrections for the energy schedules; transferring said proposed correction to the distributed ledger; transferring said proposed correction to the utility which decides to use or not to use the proposed correction. By deciding to use the proposed correction, the schedules are corrected and information is transferred from the utility to the computing means.