A Comprehensive Benchmark Platform for Process Control Research of Outdoor Microalgae Raceway Reactors

TL;DR

This paper introduces a comprehensive, open-source benchmarking platform for evaluating control strategies in outdoor microalgae raceway reactors, integrating realistic models, disturbances, and performance metrics.

Contribution

It provides a high-fidelity simulation environment with standardized interfaces for comparing various control methods in outdoor algal bioprocesses.

Findings

Baseline controllers demonstrate the platform's capability to evaluate control performance.

The benchmark enables quantitative comparison of classical and advanced control strategies.

The platform facilitates development of robust multivariable control for disturbance-rich environments.

Abstract

This paper presents a benchmarking framework to evaluate process control strategies in outdoor microalgae raceway reactors, integrating four key control regulation tasks: pH, dissolved oxygen (DO), culture volume through coordinated harvest-dilution actions, and temperature via a sump-mounted spiral heat exchanger. The benchmark is built upon a high-fidelity, experimentally calibrated dynamic model that captures the strongly coupled thermal, physicochemical, and biological processes governing industrial-scale open raceway ponds. A closed-loop simulation environment is provided, featuring realistic actuator constraints, gas transport delays, stiff integration, and a fully specified scenario based on multi-day outdoor disturbances (irradiance, temperature, wind, and humidity). Four user-replaceable controllers define the manipulation of CO2 injection, air bubbling, harvest/dilution sequencing, and heat-exchanger operation. The platform computes a unified global performance index, in addition to individual metrics for each control problem, combining tracking error, gas and energy usage, and biomass productivity, enabling consistent and quantitative comparison of alternative control strategies. Baseline regulatory architectures (On/Off, PI/PID, and Economic Model Predictive Control (EMPC)) are included to illustrate the benchmark use for classical and advanced control methods. By providing an openly specified, reproducible, and computationally tractable benchmark with well-defined function interfaces, this work aims to bridge control methodology and outdoor algal bioprocess engineering, and to support the development of multivariable control strategies for disturbance-rich environmental systems.