# Design and Development of a Management System for Energy Microgrids Using Linear Programming
## 3 Results  
According to the proposed experiments in each scenario, the analysis of the results is carried out in order to evaluate research hypotheses and review the sensitivities of the response variables regarding changes in the configuration and working conditions to which they are subjected to on a microgrid.  
Figure 1 shows, for one of the experiments, the hourly balance of the load and each energy resource on the microgrid. This figure shows a trend, which is repeated for all scenarios, in the use of renewable generation resources as the operating base of the microgrid, ensuring that through this generation of renewable energy, renewable resources are used for 100% of the time that they are available, despite the need for a diesel source in all periods during the day, given that its total operating cost is higher than the other sources.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Component** & **Scenario 1** & **Scenario 2** & **Scenario 3** & **Scenario 4** \\ \hline Demand (\(d_{l}\)) & \([0.75*d,1*d,1.25*d,\) \(1.25*rushhour]\) & \([1*d]\) & \([1*d]\) & \([1*d]\) \\ Diesel capacity & \([0.8*d_{max}]\) & \([0.8*d_{max}]\) & \([0.8*d_{max}]\) & \([0.8*d_{max}]\) \\  & \([0*d,0.05*d,0.1*d,\) \(0.3*d]\) & & \\ Solar capacity & \([0.3*d]\) & \(0.15*d,0.20*d,\) \(0.3*d]\) & \([0.3*d]\) & \([0.3*d]\) \\  & \(0.25*d,0.3*d]\) & & \\  & \([0*d,0.05*d,0.1*d,\) \(0.15*d,\) \(0.15*d,\) \(0.20*d,\) & \([0.3*d]\) & \([0.3*d]\) \\ Wind capacity & \([0.3*d]\) & \(0.15*d,0.20*d,\) \(0.25*d,\) \(0.3*d]\) & \([0.3*d]\) \\  & & \(0.25*d,0.3*d]\) & & \\ Battery capacity & \([500]\) & \([500]\) & \([0.1*d_{max},0.2*d_{max},\) & \\  & \(0.3*d_{max}]\) & & \([500]\) \\ \(L_{min}\) & \([2]\) & \([2]\) & \([0,1,2]\) & \([2]\) \\ \(L_{max}\) & \([2]\) & \([2]\) & \([0,1,2]\) & \([2]\) \\ \(eb_{max}\) & \([100]\) & & \([0.2*ub),0.35*ub,\) & \\  & \(0.45*ub]\) & & \([100]\) \\ \(g_{B}^{max}\) & \([100]\) & & \([0.2*ub,0.3*ub,\) & \\ Unattended demand & & & \(0.6*ub]\) & \\  & cost & \([1.6*Diesel_{cost}]\) & \([1.6*Diesel_{cost}]\) & \([0.8-1.2*Diesel_{cost}]\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sets of experimental conditions.  
Additionally, it shows that after the availability of renewable resources increases in a certain hour, charging processes start at the battery storage system. This process of storing energy from different generation sources starts just before of the disappearance of the generation from the solar source (which is the most available renewable generation source), so it can be understood that the model identifies a lack of energy generation at night time and tries to supply it by storing energy at the battery system to meet future demand.  
Likewise, the model uses the energy produced and stored when the renewable sources decrease, as expected. In particular, it makes use of stored energy at times when solar generation is not available. In the same way, it uses renewable generation and allows for the modulation of attention to demand with the diesel generator, which in each period of time is available for regulation by the operator.