Distributed Energy Communication Protocol for Heterogeneous Grid Control
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Solution Overview
Problem
Distributed energy management systems with heterogeneous power generation and storage systems face challenges in optimizing resource allocation across multiple independent owners with conflicting priorities, requiring a communication protocol that can dynamically balance generation and storage costs in diverse environments.
Innovation Solution
A communication protocol that uses a reduced command set combined with a cyclic perturbation technique to optimize system-wide resource allocation, implemented with master and slave communication modules that coordinate power generation and storage actions across the network, allowing for dynamic adjustment based on real-time sensor data and local rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a communication protocol with a reduced command set is used, then device complexity is reduced and ease of operation is improved, but the ability to manage heterogeneous systems with multiple owners and conflicting priorities becomes more difficult
Solution Approach 1:
The system segments the heterogeneous network into multiple zones or areas, each managed by a local controller that handles owner-specific priorities and preferences. These local controllers communicate with a central controller using the simplified protocol, effectively dividing the complex management task into manageable segments while maintaining overall system coordination.
Solution Approach 2:
Local controllers act as intermediaries between the simplified communication protocol and the complex heterogeneous systems. These intermediaries translate simple commands into appropriate actions for diverse power generation and storage systems, reconciling conflicting owner priorities without requiring the protocol itself to become complex.
2Reliability
If a central controller manages all power generation and storage systems, then system-wide coordination is improved, but the system becomes less adaptable to local owner preferences and priorities
Solution Approach 1:
The control architecture is segmented into hierarchical levels: a central controller that ensures system-wide reliability and coordination, and local controllers that handle owner-specific preferences and priorities. This segmentation allows both central coordination and local adaptability to function simultaneously without conflict.
Solution Approach 2:
Different parts of the system have different control qualities: the central controller provides system-wide coordination for reliability, while local controllers provide customized response to individual owner preferences. Each level performs the type of control best suited to its scope and requirements.
3Productivity
If cyclic perturbation technique is used for optimization, then system-wide optimization of storage versus generation costs is achieved, but the system requires more complex communication and control mechanisms
Solution Approach 1:
The system implements dynamic optimization through cyclic perturbation, where the central controller periodically adjusts operational parameters to explore different cost configurations. This dynamic approach allows the system to adapt to changing conditions and find optimal cost balances between storage and generation without requiring permanently complex control mechanisms.
Solution Approach 2:
Cyclic perturbation applies periodic adjustments to system parameters rather than continuous complex control. The central controller implements regular optimization cycles that temporarily perturb operational settings, evaluate results, and revert to optimal configurations, achieving cost optimization through simple periodic actions rather than continuously complex mechanisms.
Data Source
AI summary
A system, a device, a method, a communication protocol, and/or the like, for energy management in a fragment, heterogeneous, electrical grid. The grid may include multiple types of power generation systems, electrical energy storage systems, electrical loads, and efficiently managing these systems may require elements that will bridge the technology gap of these systems, as well as provide best-effort power generation and consumption in order to stabilize the grid. These techniques are especially important in differentiated electric energy networks, such as micro-grids, island grids, virtual power plants, and/or the like.