Model Predictive Control for Hydroelectric Power Plant Reservoirs

The present work describes a project aimed to the optimization of the water management within the reservoirs of a hydroelectric plant located in Italy. The considered reservoirs feed a set of turbines for energy production. The nature of the process and the availability of forecasts on water requests by the hydroelectric plant motivated the choice of a Model Predictive Control strategy. A first principle linear model with time delays has been adopted for the process modellization; the relationship between the sensor level information and reservoir water volume has been suitably identified from data. A tailored strategy for taking into account unknown water flows has been developed. The MPC strategy has been designed based on the obtained linear model and on assigned control specifications. In particular, special attention has been given not to waste water and at the same time to guarantee a prompt reaction to possible variation of the electric energy production plan. The reliability of the proposed approach has been tested through tailored simulation experiments, taking into account different significant scenarios. The developed proprietary framework has been installed on the real plant, confirming the validity of the designed control strategies.

I. Introduction

The hydroelectric sector is experiencing strong growth in global production, also thanks to the use of the latest technologies available, with particular attention to the monitoring part of electricity production and the correct use of water resources. Among the various types of sustainable energy, hydroelectric is the oldest (the first installation dates back to 1870) and is the most widespread globally; it is in fact the main alternative to fossil fuels, covering most if not all of the national energy needs. The principle of hydroelectric energy production is to exploit the force and action of large masses of water, moved by gravity inside penstocks, to generate electricity. In fact, falling or moving water guarantees kinetic energy, which in turn is transformed into electricity thanks to turbines and alternators. According to data from the International Renewable Energy Agency (IRENA) for 2020, the total power of hydroelectric plants in the world is about 1332 GW, while that of the entire renewable sector is around 2800 GW. In other words, hydroelectric energy production alone accounts for nearly the production of all other renewable energies added together [1]. If on the one hand renewable hydroelectric energy is a resource largely already exploited, on the other it assumes strategic importance for the years to come (just think, for example, of the European projects on energy sustainability to be implemented by 2030). In a rapidly changing energy context, hydroelectricity has therefore not remained behind, and has aimed and continues to enhance the opportunities offered by new technologies to optimize efficiency and safety; today, in fact, the control units are equipped with increasingly advanced digital systems for management, monitoring and maintenance (classic and predictive). Data collection is a fundamental step, using wireless sensor networks capable of collecting and transmitting in real time all the information on a hydroelectric plant, both on the hydraulic and on the electrical front. The information can then be sent to specific cloud platforms, stored in the data lake and then processed with statistical algorithms to promptly identify any malfunctions, avoid failures, maximize production and reduce costs. Digitization also brings benefits for the energy efficiency of power plants, using specially developed codes and software to optimize the performance of hydroelectric turbines and the use of available water [2]