Bioprocess Innovator Relies on Process Modeling to Optimize Algae-to-Biofuel Conversion
Company Size
11-200
Region
- Pacific
Country
- Australia
Product
- aspenONE Engineering Desktop
- Aspen Plus
- Aspen Process Economic Analyzer
Tech Stack
- Process Modeling
- Techno-economic Analysis
Implementation Scale
- Pilot projects
Impact Metrics
- Environmental Impact Reduction
- Innovation Output
Technology Category
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Process Analytics
Applicable Industries
- Renewable Energy
Applicable Functions
- Product Research & Development
Use Cases
- Predictive Quality Analytics
- Process Control & Optimization
Services
- Software Design & Engineering Services
About The Customer
Pan Pacific Technologies is a specialized engineering consultancy based in Adelaide, Australia that focuses on new sustainable energy solutions. They have developed proprietary concepts and intellectual property for the commercialization of capturing and converting carbon to biofuels and other products using algae. The company recently joined the National Alliance for Advanced Biofuels and Bioproducts (NAABB), a consortium which is investigating innovations in processes using algae for the production of biofuels under a major U.S. Department of Energy research grant.
The Challenge
Pan Pacific Technologies, a small company with powerful thought leadership in the area of algae to biofuels conversion, was seeking a rigorous approach to validate the technical and economic feasibility of its proprietary algal conversion concepts. A key challenge was to find a modeling environment that would provide an effective way to capture and communicate their proprietary ideas to researchers worldwide. They needed to simulate a complex biological system that was previously difficult to model, improve understanding of process constraints and scale-up, and complete techno-economic analysis.
The Solution
Pan Pacific Technologies put their algae process knowledge, which previously had been modeled in Microsoft Excel, into an Aspen Plus model. They experienced a breakthrough by predicting key limiting factors, allowing them to create a placeholder for otherwise unavailable algae property data. Through innovative use of aspenONE solutions, Pan Pacific Technologies was able to successfully produce an Aspen Plus model with results matching laboratory and industry data. With this baseline case, they further used the model, the energy balance, and the link to AspenTech’s estimating system to understand scale-up constraints and the key economics of the process.
Operational Impact
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Vestas: Turning Climate into Capital with Big Data
Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.
Case Study
Siemens Wind Power
Wind provides clean, renewable energy. The core concept is simple: wind turbines spin blades to generate power. However, today's systems are anything but simple. Modern wind turbines have blades that sweep a 120 meter circle, cost more than 1 million dollars and generate multiple megawatts of power. Each turbine may include up to 1,000 sensors and actuators – integrating strain gages, bearing monitors and power conditioning technology. The turbine can control blade speed and power generation by altering the blade pitch and power extraction. Controlling the turbine is a sophisticated job requiring many cooperating processors closing high-speed loops and implementing intelligent monitoring and optimization algorithms. But the real challenge is integrating these turbines so that they work together. A wind farm may include hundreds of turbines. They are often installed in difficult-to-access locations at sea. The farm must implement a fundamentally and truly distributed control system. Like all power systems, the goal of the farm is to match generation to load. A farm with hundreds of turbines must optimize that load by balancing the loading and generation across a wide geography. Wind, of course, is dynamic. Almost every picture of a wind farm shows a calm sea and a setting sun. But things get challenging when a storm goes through the wind farm. In a storm, the control system must decide how to take energy out of gusts to generate constant power. It must intelligently balance load across many turbines. And a critical consideration is the loading and potential damage to a half-billion-dollar installed asset. This is no environment for a slow or undependable control system. Reliability and performance are crucial.
Case Study
Remote Monitoring and Control for a Windmill Generator
As concerns over global warming continue to grow, green technologies are becoming increasingly popular. Wind turbine companies provide an excellent alternative to burning fossil fuels by harnessing kinetic energy from the wind and converting it into electricity. A typical wind farm may include over 80 wind turbines so efficient and reliable networks to manage and control these installations are imperative. Each wind turbine includes a generator and a variety of serial components such as a water cooler, high voltage transformer, ultrasonic wind sensors, yaw gear, blade bearing, pitch cylinder, and hub controller. All of these components are controlled by a PLC and communicate with the ground host. Due to the total integration of these devices into an Ethernet network, one of our customers in the wind turbine industry needed a serial-to-Ethernet solution that can operate reliably for years without interruption.
Case Study
Temperature monitoring for vaccine fridges
Dulas wanted a way to improve the reliability of the cold chain, facilitating maintenance and ensuring fewer vaccines are spoiled. Dulas wanted an M2M solution which would enable them to record and report the temperature inside vaccine refrigerators.
Case Study
IoT Powering A New Way to Light Streets with Bifacial Solar Panels
When James Meringer’s commercial contracting business experienced a rapid increase in solar projects, he also saw an opportunity to extend the benefits of solar by using the bifacial solar panels he’d become familiar with in new ways. Bifacial solar panels enable sunlight from both sides of the panel, making it a more efficient harvest of solar power. Seeing the panel’s power, James and his team set out to use the same technology for street lighting. Until now, solar street lights have served as utilitarian solutions that force designers to choose between form and function. The Mira Bella Energy team has changed that.
