ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study

Abstract

Water Supply Systems (WSS) are large consumers of energy mainly used in pumping stations and treatment plants. Therefore, the improvement of energy efficiency is a major priority for water utilities. The current research work presents a new methodology and a computational algorithm based on renewable energy concepts, hydraulic system behaviour, pressure control and neural networks for the determination of the best hybrid energy configuration to be applied in a typical water supply system. The Artificial Neural Network (ANN) created to determine the best hybrid system uses scenarios with only grid supply, grid combined with hydro turbine, with wind turbine and mutual solutions with hydro and wind turbine. The ANN is trained based on values obtained from a configuration and economical simulator model (CES), as well as from a hydraulic and power simulator model (HPS). The results obtained show this ANN advanced computational model is useful for decision support solutions in the plan of sustainable hybrid energy systems that can be applied in water supply systems or other existent hydro systems allowing the improvement of the global energy efficiency. A real case study is analysed to determine the best sustainable hybrid energy solution in a small WSS of Portugal.

Efficient Energy Management for the Smart Sustainable City Multifloor Manufacturing Clusters: A Formalization of the Water Supply System Operation Conditions Based on Monitoring Water Consumption Profiles

“…At the same time, water losses in water supply networks are significant (e.g., in the EU they account for 24% of the total amount of water consumed [15]). Improving the efficiency of water and electricity consumption in the megapolis WSS under water scarcity and climate change problems is a priority task for water supply companies [6,62,65,66].…”

“…The features of the water supply process, in particular, the use of water as a product and as a natural resource, not only determine the efficiency of electricity use in individual structural elements but also affect the efficiency of energy resource use in the WSS as a whole. The pumping stations subsystem, which ensures water pumping, is the largest consumer of electrical energy among the subsystems involved in the water supply process [5,60,[63][64][65][66][67][68]. The electricity consumption for pumping water depends on the volume of pumped water and the generated head (pressure).…”

Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks

“…Therefore, for the training of neural networks, it is necessary to create a set of data on hourly water demand. For all the above reasons, the random normal distribution with a base value of 5 L/s is chosen, which is described in Equation (1).…”

“…Water pressure management is one of the main issues in water distribution networks (WDNs) as it is related to water and energy saving [1]. High-pressure values are directly connected to leaks, water losses, and damage of pipes, especially in old WDNs [2].…”

PAT Design Strategy for Energy Recovery in Water Distribution Networks by Electrical Regulation

“…Therefore, the number of pressure reducing valves currently being used is increasing. The replacement of pressure reducing valves with hydropower devices [8,9] could lead to large energy savings [10]: an available study estimates the available energy in the UK water industry equal to about 17 MW [11].…”