Uncertainty-flexibility matching engine for electric energy
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Solution Overview
Problem
Electric power grids face inefficiencies and system failures due to variability and uncertainty in renewable energy production and consumer demand, lacking products that address uncertainty in electricity volume, leading to potential energy imbalances and infrastructure costs.
Innovation Solution
A system that matches uncertainty with flexibility by using a quantitative description of flexibility and uncertainty, allowing for proactive hedging through a market that includes inter-temporal constraints, accessible to all participants, utilizing a zonotopic mapping to generate control signals for energy consumption and production adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If renewable energy production and decentralized generation are increased, then energy sustainability and distribution are improved, but uncertainty in supply and demand increases
Solution Approach 1:
The system performs preliminary matching of flexibility offers and requests before uncertainty realizations occur. By proactively identifying and contracting flexibility resources in advance, the system prepares compensation mechanisms ahead of time, reducing the impact of supply-demand uncertainties without requiring reactive infrastructure changes.
Solution Approach 2:
The matching engine acts as an intermediary between uncertain energy units (generators/consumers facing uncertainty) and flexible energy units (resources that can adjust). This intermediary matches flexibility needs with available flexibility resources, enabling uncertainty management through coordinated control signals without direct peer-to-peer complexity.
2Reliability
If grid-reinforcement and infrastructure upgrades are implemented, then system reliability is improved, but cost and implementation time increase significantly
Solution Approach 1:
The system enables flexible energy units to self-adjust their operation based on control signals from the matching engine. These units autonomously provide frequency regulation and uncertainty compensation services, eliminating the need for expensive grid reinforcement while maintaining system reliability through distributed self-service capabilities.
Solution Approach 2:
The system changes operational parameters of existing flexible energy units (generation/consumption levels, timing) to provide grid stabilization services. By adjusting these parameters dynamically based on uncertainty realizations, the system achieves reliability improvements without physical infrastructure changes.
3Productivity
If demand-response programs with variable pricing are implemented, then cost-effectiveness is improved, but reliability decreases due to unknown price elasticity
Solution Approach 1:
The matching engine implements feedback by continuously monitoring flexibility offer utilization and matching outcomes. This feedback mechanism allows the system to learn from actual flexibility responses rather than relying on uncertain price elasticity assumptions, improving both cost-effectiveness and reliability through data-driven optimization.
4Adaptability or versatility
If multi-stage markets are implemented, then uncertainty management is improved, but system complexity and accessibility limitations increase
Solution Approach 1:
The system merges flexibility offer matching, control signal generation, and uncertainty compensation into a single integrated matching engine. This consolidation simplifies the market structure by combining multiple functions into one system, reducing complexity while maintaining comprehensive uncertainty management capabilities.
Solution Approach 2:
The matching engine serves multiple functions simultaneously: it matches flexibility offers with requests, generates control signals for flexible units, manages uncertainty compensation, and provides a trading platform. This multi-functionality in a single system reduces overall market complexity while maintaining versatility in uncertainty management.
Data Source
AI summary
Exemplary embodiments relate to a matching engine for the coordination of electric energy production and consumption, in particular in the presence of uncertainty. The engine provides matching based on uncertainty and flexibility in the electric supply and demand chains. The system can use quantified characterizations of uncertainty and flexibility provided by performance measurements of the elements in the chain.


