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

In this paper, the possibility of installing small hydraulic turbines in existing water-supply networks, which exploit the daily pressure fluctuations in order to produce energy, is examined. For this purpose, a network of five pressure sensors is developed, which is connected to an artificial intelligence system in order to predict the daily pressure values of all nodes of the network. The sensors are placed at the critical nodes of the network. The locations of the critical nodes are implemented by applying graph theory algorithms to the water distribution network. EPANET software is used to generate the artificial intelligence training data with an appropriate external call from a Python script. Then, an improvement model is implemented using the Harmony Search Algorithm in order to calculate the daily pressure program, which can be allocated to the turbines and, consequently, the maximum energy production. The proposed methodology is applied to a benchmark water supply network and the results are presented

Developing a Harmony-based Optimization Toolbox: Application on renewable energy production.

The present study aims to develop a problem-independent, generic optimization toolkit applicable to engineering optimization problems. The authors designed a program in MATLAB environment, using a Harmony Search Algorithm (HSA) in its core. A Java-based Optimization Toolkit has also been developed, taking advantage of the inherent features of object-oriented Java. Both programs allow for optimization using the HSA, which is a recent development among metaheuristics, inspired from the music creation process. Since its presentation in 2001, HSA has attracted the interest of those involved in the optimization field and thus has been successfully applied in different implementations. HSA was initially designed to optimize urban water distribution networks. Since then its application has expanded to a remarkably wide range of scientific disciplines. Although the authors’ intention is to address water engineering, hydroelectric energy production and renewable energy related problems, the created tool is generic and can be applied to any scientific field. In section 2 the authors present the up-to-date related work i.e. recent approaches in developing tools to facilitate optimization processes. The architecture of both Toolkits is presented in detail along with the main characteristics of the programs in Section 3. In Section 4 a renewable energy production problem is optimized using HSA Toolkit. This problem deals with maximizing the benefits derived from electricity production of a mini-scale hydroelectric station in a rural area. The successful convergence to best management practices proves that in addition to being user-friendly, the created tool is also very effective.JRC.F.7-Renewables and Energy Efficienc