Abstract
This paper addresses the energy management of a standalone renewable energy system. The system is configured as a microgrid, including photovoltaic generation, a lead-acid battery as a short term energy storage system, hydrogen production, and several loads. In this microgrid, an energy management strategy has been incorporated that pursues several objectives. On the one hand, it aims to minimize the amount of energy cycled in the battery, in order to reduce the associated losses and battery size. On the other hand, it seeks to take advantage of the long-term surplus energy, producing hydrogen and extracting it from the system, to be used in a fuel cell hybrid electric vehicle. A crucial factor in this approach is to accommodate the energy consumption to the energy demand and to achieve this, a model predictive control (MPC) scheme is proposed. In this context, proper models for solar estimation, hydrogen production, and battery energy storage will be presented. Moreover, the controller is capable of advancing or delaying the deferrable loads from its prescheduled time. As a result, a stable and efficient supply with a relatively small battery is obtained. Finally, the proposed control scheme has been validated on a real case scenario.
Highlights
One of the most important elements in the modern is energy, which has usually been obtained from fossil fuels
The solar photovoltaic system includes a PV array mounted on a two-axis solar tracker, which continuously changes the surface slope (β) and azimuth angle (γ) in order to minimize the angle of incidence and to maximize the solar irradiance captured by the panels
In order to introduce some disparity between the model predictive control (MPC)’s estimation and the simulation, the system will be subject to an experimental profile of solar irradiance, using data measured at the panels pyranometer
Summary
For the formulation of the control problem, it is convenient to define the controllable inputs and the measured variables needed by the controller. The controllable inputs can be characterized as follows: PSOL : Real variable depicting the electrical energy introduced to the system through the inverters of the solar panels. Note that this variable will be bounded by the available solar energy; vd : Binary signal that activates the time flexible load d. In order to compute the control action, the controller needs to have some knowledge about the state of the system. In order to estimate the solar irradiance (Ics ), it is necessary to compute the daily mean of the atmospheric turbidity (TL,n−1 ).
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