Optimització del consum energètic en ferrocarrils, a partir del control de les càrregues auxiliars

Resumen

Introduction The aim is to solve the recovery of waste energy problem, in braking periods on railway electrical vehicles, by means of a load behaviour analysis, and in particular, in air conditioning systems (HVAC), as higher consumption load (15% of total). With the control and model introduced, we work on an energy storage system located at the same HVAC unit. The feasibility of the application is on the urban and sub-urban electric railways, due to the high depart/braking cycle frequency and the high consumption. Feasibility and background The HVAC control experiences to search energy efficiency are based on knowledge of the heating load. We know almost 75% of the global load, with good accuracy. All the simulations still are developed on very simplified scenarios. True application is still difficult to demonstrate. If we research a storage control during a trip, and its relation with a closed loop thermal system control, then we have to dispose of a predictive control, in a superior level of the management hierarchy, joint to the consumption data from the vehicle. The saving proposal is based on the future and past information availability, in order to get profit from the inertia of the system, and also the energy cost cycle. We set a predictive control at vehicle level, with constraints, an optimisation function and a control law. Also some expert rules. In order to get the energy saving, we need second order systems. Also we have to manage main non-lineal issues. Formulation of the problem The calculated variable is the supply airflow temperature and the minimum power, applied to the model. We use the formulations for the mass and also for the sensible and latent energy. It¿s recommended the fresh air control, based on three concepts: free cooling, heating recovery, control of passenger occupancy. We perform energy equations by means of an equivalent representation of the electrical circuit, as a second order system. As we are working with a semi-insulated system, so the searched solution using electrical circuits simulation tools, don¿t work. The objective function to minimise has two terms, the quadratic differences of temperature and the energy applied. Strategy of the control It consists in to apply the minimum energy to the plant, which is calculated from the cost function, taking in account the prediction of the model and the comfort set point. The defined amount of reheating power can be minimised also in our control. It is demonstrated the stability of the system as second order model. With the application to the tramway case, a lot of subjects have been confirmed using MATLAB. With this tool, we are performing a specific MPC programation. Development of thermal storage system The proposed storage system takes profit of the solid-liquid phase change heating of wate besides to evaporator coil, with an absorption-evaporation cycle. With a predictive adaptive control, it makes the prediction of the required load in the vehicle, so it manages the availabl energy. During the braking period time, the obtained energy is used to apply mainly on the compresso (of variable speed), achieving the maximum capacity, and generating a big flow of hot refrigerant gas. It¿s chosen an absorption cycle to absorb the entire compressor dischargin capacity of the flux. During the traction and coasting mode, the thermal machine will try to us the minimum amount of energy to go on running. We use the same lubricant oil as absorbent. The predictive control will do a monitorisation of the required power, the driving mode, speed status and health of the accumulator, and it will calculate the key variables for the controller o second level: supply airflow temperature and minimum power to apply and the operatio mode.