# Energy Management of a Multi-Source Power System
###### Abstract  
This work focuses on energy management for a system operated by multiple energy sources which include batteries, super capacitors, a hydrogen fuel cell, and a photovoltaic cell. The overall objective is to minimize the power consumption from all sources needed to satisfy the system's power demand by optimizing the switching between the different energy sources. A dynamic mathematical model representing the energy sources is developed taking into account the different constraints on the system, i.e., primarily the state-of-charge of the battery and the super capacitors. In addition to the model, a heuristic approach is developed and compared with the mathematical model. Both approaches were tested on a multi-energy source ground robot as a prototype. The novelty of this work is that the scheduling of an energy system consisting of four different types of sources is compared by performing analysis via dynamic programming, and a heuristic approach. The results generated using both methods are analyzed and compared to a standard mode of operation. The comparison validated that the proposed approaches minimize the average power consumption across all sources. The dynamic modeling approach performs well in terms of optimization and provided a superior switching sequence, while the heuristic approach offers the definite advantages in terms of ease of implementation and simple computation requirements. Additionally, the switching sequence provided by the dynamic approach was able to meet the power demand for all simulations performed and showed that the average power consumption across all sources is minimized. b 2021 the authors, the fuel economy was apparently improved by a factor of three. Further, it is important to note that, the integration of multiple types of energy sources is not only important for electric vehicles. But, this is also of definite importance when considering islanded micro grid systems, where the objective is to have a variety of types of energy systems available to meet demand specifically in the absence of a main power grid [5]. Currently even traditional power grids are incorporating multiple different renewable energy sources and batteries [6]. The main principle in energy management of such systems with many different energy sources, is efficiently matching the demand and supply of power in the system. The main challenge faced is determining in what proportion each of the available sources is used to ensure that enough power is available to meet the demand in the system. The process is tedious because of the different characteristics of the various sources integrated into a multi-source power system. The behavior of the power sources must be taken into account to achieve efficient management of the sources. Drones are ubiquitous, and future drones/flight systems could benefit from multiple onboard energy sources. Drones are used by delivery companies [7; 8], as well as by photographers. They are also being used in the medical field to deliver automated external defibrillators to out-of-hospital cardiac arrest patients [9]. Most commercial drones are equipped only with a single lithium-ion battery that allows a maximum flight time of about thirty minutes, mostly less [10]. Presently, researchers are attempting to incorporate multiple renewable and sustainable energy sources in drones [11]. While successful integration of multiple energy sources for long duration flight remains to be researched, as reported in the works above, there are many avenues where utilizing multiple energy sources improves efficiency. This also extends the duration of usage of such a multi-source power system compared to one that uses a single source of a specific type. Thus, this work is concerned with optimizing the energy management of a system that contains four different types of power sources. The objective is to optimize the scheduling of the switching sequence of the sources to minimize the power dissipation in the system and ensure meeting the power demand.