## 5 Experimental Results  
To ensure proper manipulation, it was first necessary to test and calibrate the feedback sensors connected to the R&D board's ADCs and its PWM channels controlling the power switches involved. Current control was tested, where all the different sources were able to participate successfully in supply power to the DC bus. A programmable load was configured in CV mode to absorb current and prevent overvoltage on the DC bus. The software used simulated the consumption profile and availability of renewable energies producing appropriate set points for the corresponding power converters. The experiment conducted seeks to emulate as many real physical parts as possible, in cases where physical parts were unavailable, an integrated software component was used as a substitute. In this particular example, the setup (in Figure 20) is made of five main parts; the main group of hardware consist of (1) the current controlled 30 V, 3 A voltage sources representing the LCG, battery (discharge mode), wind driven power plant and solar panel. (2) The programmable load (PL) AEL-5000 is used as a dummy load to emulate the consumer demand. While it is possible to control the current going to the PL via an Ethernet medium, instead it is set in constant voltage (CV) mode, then it is connected to the bus via a boost converter according to the schematics in Figure 21 subsequently resulting in faster run time. (3) and (4) current controlled DC-DC converters. (5) computational system for the implementation of the software part, the availability of renewables is inferred in a predetermined in the software used as lookup tables; this provides a necessary degree of freedom in order to direct the experiment more efficiently and in a timely manner. The \begin{table}
\begin{tabular}{c c c c} \hline \hline
**I vr (pu)** & **I rs (pu)** & **Local Cost (pu)** & **J Flat (pu)** \\ \hline
0 & 0.8 & 12.8457 & 0.2526 \\
0.05 & 0.68 & 11.9649 & 0.2955 \\
0.08 & 0.6 & 9.6683 & 0.3356 \\
0.15 & 0.5 & 6.8976 & 0.5126 \\
0.2 & 0.4 & 4.6929 & 0.7534 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Local cost function correlation to the choice of charging and discharging battery currents. Figure 19: MATLAB SIMULINK simulation inertial response for K = 2 and K = 1000.  
battery response is emulated thanks to the combination of software model that output reference points in real-time and hardware consisting of for CCS for discharging and buck in conjunction with a resistor for charging. The CV mode parameter is set to 75 V, while the bus voltage is regulated at 60 V, hence ensuring that the PL does not participate in voltage regulation. Finally, the dSPACE DS1104 R&D Controller Board, where all the developed controller, system models, look up table and algorithm are deployed in accordance with the previously review theoretical content. Figures 22 and 23 display the evolution of the bus's voltage in time, as it can be observed the controller retains the voltage in its tolerance zone indicating the suitability of the control scheme used for this application. Figure 21: Experimental schematics of the MG.  
Figure 20: Test bed laboratory set up. Figure 22: Experimental results of MG’s bus voltage. Figure 24 could be considered the highlights of this paper's work, the experimental results disclosed are similar to those in the simulation because variables such as wind and solar availability as well as the CP are recorded in lookup tables and then inserted as set point in time for the current controlled sources and bus. It is entirely feasible to replicate the currents observed in the simulation within an experimental setup. The consumption profile current, solar panel current, and wind generation current are elements of the experiment itself, from the simulation, data has been stored in a lookup table in MATLAB SIMULINK then subsequently used as set points for current control of the ensemble (DC source + DC-DC converter), resulting in identical appearances.