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Supervisory Control of Hybrid Power Plants Using Online Feedback Optimization: Designs and Validations with a Hybrid Co-Simulation Engine

Sayak Mukherjee, Himanshu Sharma, Wenceslao Shaw Cortez, Genevieve Starke, Michael Sinner, Brooke J. Stanislawski, Zachary Tully, Paul Fleming, Sonja Glavaski

TL;DR

The paper develops a supervisory controller for wind–solar–battery hybrid power plants using online feedback optimization to track load demands despite weather uncertainty. It formulates the control problem in a model-free, gradient-based framework where the plant subsystems are treated as input–output mappings and the supervisor updates setpoints at a slower timescale, constrained by real-time available power from wind, solar, and storage. The approach is integrated into the WHOC framework and validated within the Hercules co-simulation engine, demonstrating robust demand tracking and efficient battery usage under realistic resource profiles. This work advances real-time, uncertainty-robust dispatch for hybrid plants and provides a pathway to operationally integrating supervisory FO control with detailed co-simulation and planning layers.

Abstract

This research investigates designing a supervisory feedback controller for a hybrid power plant that coordinates the wind, solar, and battery energy storage plants to meet the desired power demands. We have explored an online feedback control design that does not require detailed knowledge about the models, known as feedback optimization. The control inputs are updated using the gradient information of the cost and the outputs with respect to the input control commands. This enables us to adjust the active power references of wind, solar, and storage plants to meet the power generation requirements set by grid operators. The methodology also ensures robust control performance in the presence of uncertainties in the weather. In this paper, we focus on describing the supervisory feedback optimization formulation and control-oriented modeling for individual renewable and storage components of the hybrid power plant. The proposed supervisory control has been integrated with the hybrid plant co-simulation engine, Hercules, demonstrating its effectiveness in more realistic simulation scenarios.

Supervisory Control of Hybrid Power Plants Using Online Feedback Optimization: Designs and Validations with a Hybrid Co-Simulation Engine

TL;DR

The paper develops a supervisory controller for wind–solar–battery hybrid power plants using online feedback optimization to track load demands despite weather uncertainty. It formulates the control problem in a model-free, gradient-based framework where the plant subsystems are treated as input–output mappings and the supervisor updates setpoints at a slower timescale, constrained by real-time available power from wind, solar, and storage. The approach is integrated into the WHOC framework and validated within the Hercules co-simulation engine, demonstrating robust demand tracking and efficient battery usage under realistic resource profiles. This work advances real-time, uncertainty-robust dispatch for hybrid plants and provides a pathway to operationally integrating supervisory FO control with detailed co-simulation and planning layers.

Abstract

This research investigates designing a supervisory feedback controller for a hybrid power plant that coordinates the wind, solar, and battery energy storage plants to meet the desired power demands. We have explored an online feedback control design that does not require detailed knowledge about the models, known as feedback optimization. The control inputs are updated using the gradient information of the cost and the outputs with respect to the input control commands. This enables us to adjust the active power references of wind, solar, and storage plants to meet the power generation requirements set by grid operators. The methodology also ensures robust control performance in the presence of uncertainties in the weather. In this paper, we focus on describing the supervisory feedback optimization formulation and control-oriented modeling for individual renewable and storage components of the hybrid power plant. The proposed supervisory control has been integrated with the hybrid plant co-simulation engine, Hercules, demonstrating its effectiveness in more realistic simulation scenarios.
Paper Structure (14 sections, 35 equations, 9 figures, 1 table)

This paper contains 14 sections, 35 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background
  3. Hybrid Power Plants
  4. Mathematical Preliminaries to Feedback Optimization
  5. Supervisory Control Problem Formulation
  6. Methodology
  7. Resource-Specific Considerations
  8. Constraints on the Wind Subsystem
  9. Constraints on the Solar Subsystem
  10. Constraints on the Battery Energy Storage Subsystem
  11. Simulation Tests with Realistic Resource Inputs and Simplified Models
  12. Supervisory Controller Integration with a Co-simulation Hybrid Plant Engine and Validations
  13. Numerical Experiments
  14. Conclusions

Figures (9)

  • Figure 1: Implementations of offline optimization (top) and online feedback optimization (bottom) control for hybrid plant, where d is demand, u are the control inputs and y are the plant measurements.
  • Figure 2: Overview of the Wind Hybrid Open Controller (WHOC) implementation with the proposed hybrid supervisory controller (at higher level), and low-level controllers for individual plants.
  • Figure 3: Example: Maximum available power for 5 MW turbine.
  • Figure 4: An example showing the maximum available power profile based on irradiance and air temperature generated using the National Renewable Energy Laboratory's (NREL's) System Advisor Model™ pysam_24.
  • Figure 5: Hybrid plant operation scenarios under realistic conditions showing wind variability, supervisory control response, battery charging, and discharging behaviors.
  • ...and 4 more figures