Year: 2024
Type: dissertation
Abstract: The main purpose of this work was the development of energy optimization procedures for a wastewater treatment plant. Along with it, solutions were presented and analysed for economic viability. For this aim, extensive bibliographic research was undertaken to better understand the existing tools, models, and results already achieved with each set of conditions. To elaborate the case-study, data for biogas production and electricity needs of a wastewater treatment plant were retrieve. Alongside it, the Solcast API was utilized to retrieve historical data. After schematizing the functioning of the plant, a rule-based approach was selected for the simulation and optimization of energy. To guide the programming, flowcharts were designed to mimic the relations between each set of variables and components. With the intent of making the simulator have a more widespread utilization, the required programming was executed in Excel and VBA (Visual Basic for Applications). The results were broken down and analysed with the objectives of burnt biogas minimization, cost reduction, and self-sufficiency in view. Results showed a vast improvement after the introduction of the energy optimization system, with self-sustainability ratio increasing from 70% to above 91% in all analysed scenarios with both biogas and photovoltaic as renewable energy sources. The implementation of a secondary cogeneration unit was studied, to reduce the amount of burnt biogas in low-purchase scenarios. Results showed that the application of a second cogeneration unit can be profitable, if the wasted biogas is close to 25% of the total production. Similarly, the cost-effectiveness of the implementation of the photovoltaic system was also analysed, due to the high amount of exceeding energy derived from this source of energy. Two solutions were tested. The first one showed that establishing a renewable energy community with neighbouring facilities is a viable alternative to utilize the excess of produced electricity, with the internal rate of return oscillating between 38.68% and 15.45%, depending on the simulation scenario. The second analysis consisted of a sensitivity analysis of the selling price of electricity. It utilized the scenario which yielded the worst result on the previous analysis. It determined that, for selling prices higher than 0.15 €/kWh, it can be a viable option to sell the electricity back to the grid, even though it does not achieve the same economic benefits as the community approach.
Author: Gonçalves, Rúben Ramalho
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7060630308