Problem and context: How can utility businesses improve the efficacy of their wastewater systems?
Wastewater and sewage in the UK water sector is valued at £8.7 billion and employs 42,000 people. Every day it deals with over 16 billion tons of wastewater. And, increasingly, some of the wastewater is transformed into bio-resources that can be used for energy or in other industries. Presently, deregulation and competition are increasing in the wastewater sector, creating opportunities for supply chain innovations at different stages of the water treatment cycle. Utility companies are now competing against each other to manage bio-resources, making wastewater supply chains, and the efficiency of their logistics networks a massively profitable industry.
For water utility providers, it can be difficult to develop the resource efficiency of supply chains and processes, especially when considering them in the context of industrial sustainability. Configuring and testing new designs for wastewater logistics networks that transform bio-resources into useful bi-products like energy is one option, which makes economic and environmental sense; especially as it is a key resource and a contributor to maintaining and potentially improving society’s quality of life. However, achieving resource efficiency in the wastewater treatment sector requires novel models and new ways of thinking.
That is why, when a UK wastewater treatment company decided to optimize the logistics infrastructure of their facility network, they sought the expertise of decisionLab, a London consulting company that specializes in creating decision-making tools using simulation, optimization, and machine learning. decisionLab engineers needed to simulate and test the wastewater treatment supply chain in a risk-free environment, with a specific focus on novel processes, before any capital investments were made. With a wastewater treatment simulation model, they would be able to assess the utilization of different types of settlement and anaerobic digestion facilities, and optimize their quantity based on return on energy investments.The optimized configuration would lead to:
- Refined industrial ecology for the settlement, caking, and digestive processes that act as a measure of waste “upcycling loops”.
- Increased collaboration with neighboring water utilities based on anaerobic digestion capacity.
- Optimized logistics routing during the transportation of caked product, ensuring competitive advantage.
- A proof of operational sustainability for industry regulators and investors.
The key to delivering an effective wastewater treatment simulation model, in this case, was understanding the sustainability of the operation and ensuring that there was visibility of any returns on logistics and energy investments. Both would lead to a ‘net-positive’ impact. To determine this, the wastewater supply chain treatment simulation was used to forecast if the system was agile enough to minimize capital expenses and enable further infrastructure investment.
To model a network of wastewater treatment facilities, the decisionLab team applied AnyLogic simulation capabilities. This platform was a natural fit for modeling such a complex environment, with its flexible modeling tools, enabling a combination of discrete event and agent-based approaches, so the developed model could be optimized for minimum cost and maximum energy return. AnyLogic also provided excellent visualization capabilities and enabled the engineers to use GIS functionality to better display the logistics network and make the data visually compelling.
The decisionLab consultants decided to focus on: understanding the sustainability of the operation, ensuring that there was a return on wastewater treatment logistics costs, and that the energy return on investment was positive. To support the client, the consultants simulated four scenarios:
- ‘As-is’ logistics routing of bio-resource production
- Industrial ecology of settlement and caking processes with fewer centralized digestion sites
- Distributed digestion sites and how these impacted the cost of logistics
- Advanced ‘to-be’ anaerobic digestion sites vs. current ‘as-is’ technologies
As a result of the work, a wastewater treatment simulation model for the utility provider’s industrial ecology was developed. This model can be used to support network planning and prove various assumptions. It was specifically used to benchmark the following key performance indicators using the scenarios described above:
- Optimal logistic routing over a year of bio-resource production, considering seasonality
- The industrial ecology of settlement and caking processes at per-quarter granularity
- Anaerobic digestion site utilization to provide a maximum energy return on investment
The first insight was that the best-performing anaerobic digestion (AD) facilities were those with a 5-10 million-liter capacity spread out across the supply chain. This was a surprising result, as the engineering team had originally assumed, from a static analysis, that centralized larger facilities (<10 and <20-30 million-liter capacities) were more productive as they could potentially digest more, and therefore should be able to serve a higher percentage of the population. This was proven wrong using the simulation model. The second finding was that the medium size anaerobic digestion facilities were much better in terms of energy return on investment and the amount of population that the reprocessed water was serving.
DecisionLab’s work in AnyLogic fulfilled the client’s requirements. It allowed them to get a better understanding of their processes and of alternative approaches for optimizing their current supply chain with novel infrastructure and logistics methods that could maximize returns economically and ecologically.
Watch the video of Dr. Aanand Davé, presenting this case study at The AnyLogic Conference, or download his presentation.