Multi-Layer DER Control with Boundary-Checked Real-Time Dispatch
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Solution Overview
Problem
Current microgrid dispatch strategies often fail to adapt to changing conditions, leading to suboptimal operation and mismatch between forecasts and actual system conditions, which results in inefficiencies in reducing operational costs and carbon emissions while maintaining reliability and resiliency.
Innovation Solution
A multi-layer architecture for controlling distributed energy resources (DERs) is introduced, combining a forecasting and optimization system with on-site controllers for real-time control, enabling the generation of optimal set points and real-time dispatch commands to achieve economic, reliable, and sustainable operation. This architecture includes a network interface, storage system, predictive control application, site-level controllers with boundary checks, and real-time dispatch logic to adjust commands based on local conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a forecast-based optimal dispatch engine is used, then economic objectives (lower operational costs) and carbon emissions reduction are improved, but mismatch between forecasts and actual system conditions occurs leading to suboptimal operation
Solution Approach 1:
The control system is segmented into two distinct layers: a forecasting and optimization system that handles economic optimization and carbon emissions reduction, and a site-level controller that ensures operational reliability. This segmentation allows each layer to specialize in its function while working together through hierarchical control, resolving the contradiction between economic efficiency and operational reliability.
Solution Approach 2:
The site-level controller acts as an intermediary between the forecast-based optimal dispatch engine and the actual DER operation. It receives optimal set points from the forecasting system, performs boundary checks to ensure they meet local operational constraints, and generates real-time dispatch commands that maintain reliability while achieving economic objectives.
2Adaptability or versatility
If hierarchical control with multiple layers is implemented, then adaptability to changing conditions and real-time control are improved, but system complexity increases
Solution Approach 1:
The hierarchical control structure is segmented into two functional layers with clear responsibilities. The forecasting and optimization system handles high-level economic optimization, while the site-level controller handles real-time operational control. This segmentation improves adaptability without creating unnecessary complexity by ensuring each layer performs its specific function efficiently.
Solution Approach 2:
The site-level controller merges multiple functions into a single integrated unit: it receives optimal set points from the forecasting system, performs boundary checks against local constraints, generates real-time dispatch commands, and communicates with field devices. This merging reduces overall system complexity by consolidating control functions at the appropriate level.
3Productivity
If optimal set points are generated without considering local conditions, then economic optimization is improved, but mismatch with actual system conditions occurs
Solution Approach 1:
The site-level controller implements feedback by continuously monitoring local system conditions and comparing them against optimal set points from the forecasting system. When mismatches are detected, the controller adjusts dispatch commands to maintain accuracy while working toward economic optimization goals, ensuring control precision is maintained despite forecast limitations.
Solution Approach 2:
The control system applies local quality by tailoring the control approach at the site level to match local conditions. The boundary check function verifies that optimal set points are compatible with local DER capabilities and operational constraints, while the real-time dispatch logic generates commands specifically adapted to current local system state, ensuring measurement precision and control accuracy.
Data Source
AI summary
A multi-layer architecture for control of distributed energy resources (DER) includes a forecasting and optimization system and one or more site-level controllers. The forecasting and optimization system generates predictions of optimal set points and communicate the optimal set points to a site-level controller. The site-level controller includes stored instructions that, when executed, direct the site-level controller to perform a boundary check and a real-time static economic dispatch, which can include steps of receiving optimal set points from the forecasting and optimization system; comparing received optimal set points with local conditions; outputting dispatch commands for DER control according to the optimal set points when the optimal set points are within appropriate limits with respect to the local conditions; and when the optimal set points exceed the appropriate limits, generating adjusted dispatch commands and outputting the adjusted dispatch commands for the DER control.