# A Real Model of a Micro-Grid to Improve Network Stability
## 6 Conclusions  
The article discusses the physical materialization of a smart energy model (SEM, Figure 1). The SEM is a smart grid model exhibiting a significant proportion of renewable energy sources, which are further combined with intelligent control utilizing information from a smart metering subsystem. The main advantages of the proposed grid consist in its simplicity, portability, and the broader possibility of testing the control algorithm, which exploits the demand-response strategy. Conversely, the actual use of a 24 V\({}_{\text{DC}}\) grid may be interpreted as a drawback; however, a DC/AC converter can obviously be connected, and alternating loads are applicable too. The results of the tested algorithms also generally hold for networks with a higher grid voltage. To facilitate the energy transfer from the 12 V\({}_{\text{DC}}\) batteries to the grid and vice versa, we designed and characterized a special CB1 module. This block can operate as a step-up or step-down converter, and is controlled via CompactRIO and LabView.  
A micro-grid control strategy utilizing the demand-response mode was proposed and outlined within the paper; the central aspect of this approach consists in that the entire volume of energy produced through renewable sources must be effectively utilized. Thus, the analyzed method promoted the maximum use of renewable sources to decrease the current rate of CO\({}_{2}\). Another major benefit brought by the algorithm can be identified in employing the current weather forecast to predict the amount of energy in the network; this property then enables us to transfer the applicable energy between the local BATs and the main backup BAT of the grid. The designed algorithm, described in Section 4, is mainly useful in a stand-alone microgrid; its performance and results are presented in Figures 10 and 11.  
The end user will benefit mainly from the more effective consumption of energy produced by renewable sources. Further, the algorithm will switch, within a pre-selected interval (this may reduce the user's comfort, but the interval can be chosen by the user himself), appliances included in the demand-response strategy; such a feature is very convenient for multiple consumers who regularly operate various types of chargers or power banks, namely, appliances connectable to a microgrid in the demand-response mode. The actual usage of smart metering then enables us to monitor and assess the consumption of individual devices.  
The proposed hardware and software concepts were verified on one of the possible scenarios, specified in Section 5. It follows from Figure 11 that using the microgrid control approach characterized  
Figure 12: The grid voltage pattern related to time.  
in Section 4 embodied the factor to verify the pre-set goal of \"consume all you produce\". The relative voltage error during the tests did not exceed 6%, as shown in Figure 12.  
**Acknowledgments:** The authors gratefully acknowledge financial support from the Ministry of Education, Youth and Sports under projects No. LO1210--\"Energy for Sustainable Development (EN-PUR)\" solved in the Centre for Research and Utilization of Renewable Energy).  
**Author Contributions:** [PERSON] and [PERSON] performed the main research tasks and, with [PERSON], wrote the full manuscript to propose the original idea. [PERSON] and [PERSON] fabricated, modified and supplied the hardware for the grid, whereas [PERSON], [PERSON] and [PERSON] designed and materialized the micro-grid control strategy.  
**Conflicts of Interest:** The authors declare no conflict of interest.