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Real-time Optimization for Wind-to-H2 Driven Critical Infrastructures Based on Active Constraints Identification and Integer Variables Prediction

Mostafa Goodarzi, Qifeng Li

TL;DR

This work addresses decarbonizing critical infrastructures by integrating wind power, water electrolysis, hydrogen storage, and CCS into a unified W2H-CI framework. It develops a convex, large-scale mixed-integer convex program (MICP) for real-time operation and introduces ACI-IVP, a data-driven surrogate that identifies active constraints and predicts binary variables to reduce the problem to a continuous convex form solvable rapidly. The rolling 24-hour optimization with 5-minute resolution hedges wind uncertainty, and its effectiveness is demonstrated on two case studies, achieving substantial carbon-emission reductions and cost savings while reducing solution times from minutes to seconds. The framework provides a scalable pathway to net-zero energy by coordinating wind energy with water, hydrogen, and transportation networks in remote or islanded settings.

Abstract

This paper proposes a concept of wind-to-hydrogen-driven critical infrastructure (W2H-CI) as an engineering solution for decarbonizing the power generation sector where it utilizes wind power to produce hydrogen through electrolysis and combines it with the carbon captured from fossil fuel power plants. First, a convex mathematical model of W2H-CI is developed. Then, an optimization model for optimal operation of W2H-CI, which is a large-scale mixed-integer convex program (MICP), is proposed. Moreover, we propose to solve this problem in real-time in order to hedge against the uncertainty of wind power. For this purpose, a novel solution method based on active constraints identification and integer variable prediction is introduced. This method can solve MICP problems very fast since it uses historical optimization data to predict the values of binary variables and a limited number of constraints which most likely contain all active constraints. We validate the effectiveness of the proposed fast solution method using two W2H-CI case studies.

Real-time Optimization for Wind-to-H2 Driven Critical Infrastructures Based on Active Constraints Identification and Integer Variables Prediction

TL;DR

This work addresses decarbonizing critical infrastructures by integrating wind power, water electrolysis, hydrogen storage, and CCS into a unified W2H-CI framework. It develops a convex, large-scale mixed-integer convex program (MICP) for real-time operation and introduces ACI-IVP, a data-driven surrogate that identifies active constraints and predicts binary variables to reduce the problem to a continuous convex form solvable rapidly. The rolling 24-hour optimization with 5-minute resolution hedges wind uncertainty, and its effectiveness is demonstrated on two case studies, achieving substantial carbon-emission reductions and cost savings while reducing solution times from minutes to seconds. The framework provides a scalable pathway to net-zero energy by coordinating wind energy with water, hydrogen, and transportation networks in remote or islanded settings.

Abstract

This paper proposes a concept of wind-to-hydrogen-driven critical infrastructure (W2H-CI) as an engineering solution for decarbonizing the power generation sector where it utilizes wind power to produce hydrogen through electrolysis and combines it with the carbon captured from fossil fuel power plants. First, a convex mathematical model of W2H-CI is developed. Then, an optimization model for optimal operation of W2H-CI, which is a large-scale mixed-integer convex program (MICP), is proposed. Moreover, we propose to solve this problem in real-time in order to hedge against the uncertainty of wind power. For this purpose, a novel solution method based on active constraints identification and integer variable prediction is introduced. This method can solve MICP problems very fast since it uses historical optimization data to predict the values of binary variables and a limited number of constraints which most likely contain all active constraints. We validate the effectiveness of the proposed fast solution method using two W2H-CI case studies.

Paper Structure

This paper contains 11 sections, 6 equations, 6 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Wind-to-$H_{2}$-driven Critical Infrastructures
  3. Power Section
  4. Water Section
  5. Hydrogen Section
  6. Optimization Models for real-time operation
  7. The ACI-IVP-Based Solution Method
  8. Case Studies
  9. Evaluating the Solution Time
  10. Carbon Emission and Cost Analysis of the W2H-CIs
  11. Conclusions and Future Work

Figures (6)

  • Figure 1: The structure of W2H-CIs: $\rightarrow$ wind energy, $\rightarrow$ power, $\rightarrow$ water, $\rightarrow$ hydrogen, $\rightarrow$ carbon emission, $--$ transportation.
  • Figure 2: ACI-IVP-based surrogate transformation method
  • Figure 3: W2H-CIs for a small community such as industrial parks.
  • Figure 4: W2H-CIs for city-scale application.
  • Figure 5: Optimal operation of W2H-CIs for the second case study
  • ...and 1 more figures