Reservoir Advanced Process Control for Hydroelectric Power Production

Abstract

The present work is in the framework of water resource control and optimization. Specifically, an advanced process control system was designed and implemented in a hydroelectric power plant for water management. Two reservoirs (connected through a regulation gate) and a set of turbines for energy production constitute the main elements of the process. In-depth data analysis was carried out to determine the control variables and the major issues related to the previous operation conduction of the plant. A tailored modelization process was conducted, and satisfactory fitting performances were obtained with linear models. In particular, first-principles equations were combined with data-based techniques. The achievement of a reliable model of the plant and the availability of reliable forecasts of the measured disturbance variables—e.g., the hydroelectric power production plan—motivated the choice of a control approach based on model predictive control techniques. A tailored methodology was proposed to account for model uncertainties, and an ad hoc model mismatch compensation strategy was designed. Virtual environment simulations based on meaningful scenarios confirmed the validity of the proposed approach for reducing water waste while meeting the water demand for electric energy production. The control system was commissioned for the real plant, obtaining significant performance and a remarkable service factor.

Digitalization, Industry 4.0, Data, KPIs, Modelization and Forecast for Energy Production in Hydroelectric Power Plants: A Review

“…Data analysis, selection, storage, and acquisition can also assume a crucial role for the feasibility study of an advanced process control (APC) project in order to perform an in-depth plant inspection with the help of information related to that plant's devices [75]. Another field of application of data analysis in hydropower plants can be the evaluation of silt erosion in order to intelligently plan maintenance scheduling activities.…”

“…In order to formulate the mathematical optimization problems and to verify the performance of APC systems in hydropower plants, tailored KPIs can be formulated, monitored and analyzed [75,94]. An example of a KPI to be verified is the service factor, i.e., the time percentage associated with full service of the APC system [6,7].…”

“…Among the features needed to apply MPC, model and forecasts reliability cover a crucial role. A reliable model of the plant allows the provision of a tool with which to simulate and predict the effect of the manipulated and unmanipulated inputs on the outputs; on the other hand, forecast reliability can be referred to the availability of predictions associated with the unmanipulated inputs in order to include them in the control law computation [75]. Unmanipulated inputs can be represented by the water discharged toward the turbines, which is connected to the energy that has to be generated.…”

“…This plan is connected with the water that has to be sent to the turbines by the upstream devices. A reliable model between the hydropower generation and the provided water can provide reliable forecasts of the water that has to be discharged from the upstream devices [75]. Reliable forecasts of the water that has to be discharged from the upstream devices can be obtained through the application of different algorithms, e.g., ANFIS and the cooperative search algorithm (CSA) [152].…”

Research on joint dispatch of wind, solar, hydro, and thermal power based on pumped storage power stations

“…Literature (Gromyko et al, 2023) included the water volume constraint of the hydropower station in the modeling of hydropower stations. Literature (Zanoli et al, 2023) used a piecewise linear function to fit the hydropower conversion curve. Literature (Rahman et al, 2022) analyzed the complementarity of wind and hydropower output on a time scale and established a linear programming model for the wind-hydro joint dispatch system.…”