# Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework
## 7 Conclusions  
This paper presented an optimal dispatching schedule of a VPP for the day-ahead electricity market. The VPP integrates different renewable and nonrenewable energy sources as well as battery energy storage devices. In this study, the optimization process was carried out by using the BAS algorithm. The simulation results of the VPP using \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & **State of** & **Amount of** & **Amount of** & **Power** \\  & **Generation** & **Power Solt to** & **Purchased from** & **Inference** \\  & & **the Grid** & **the Grid** & \\ \hline \multirow{2}{*}{
\begin{tabular}{c} First \\ \end{tabular} } & All units are in \\  & ON condition. \\  & PV is assumed in \\  & fault condition. \\  & FC and battery are \\  & assumed to be in \\  & the fault condition. \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparison of the three scenarios. Figure 16: Solar generation data for three different cases considering uncertainties. the proposed algorithm were compared with those obtained by using other optimization algorithms. The simulation results proved the high-performance ability of the proposed algorithm to efficiently solve the dispatching problem. The analysis for the optimal dispatch strategy was carried out for the three scenarios. It was found from the scenarios that the grid supplies the lowest amount of power in Scenario 1 when all the power generation sources are in service. For Scenario 1, the grid supplies the power to satisfy the load demand for the first hours when the market price is low. Therefore, the VPP gets the maximum benefit from this scenario. In Scenario 2, the utility supplies the load during the first (1-8) hours, when the market price is low. Meanwhile, in Scenario 3, the utility supplies the load for 24 h regardless of the high market price, and the benefits of the VPP are the lowest in this scenario. The paper's contribution and key findings can be listed as follows:  
* The BAS algorithm is used for the optimal energy management of the VPP by reducing the total operating cost of generation. The optimal dispatch results are obtained within the minimum computation time due to its easy and simple computational process. * The day-ahead market strategy is considered with three distinct scenarios. * The attained results indicate that the VPP has to purchase the lowest amount of energy from the grid when all the generators are in the operating condition. The storage devices are allowed to charge during off-peak hours when there are less demand and discharge during peaks hours. Hence, the VPP can achieve the maximum profit by selling the energy to the grid. The development of the competitive electricity market requires an optimum model for integrating the renewable-based power generation. The adopted model assists to optimally dispatch the power among the VPP customers and with the grid. With proper scheduling of power generation from renewable energy sources, the VPP can meet the maximum demand for the day-ahead market by minimizing the power purchased from the grid and by promoting more profit to the aggregator using price-based dispatch of the power to the grid. The power trading with the grid is dependent on the profitability of the aggregator and the demand. In all the above scenarios, the renewable sources dispatched the power optimally. Conceptualization, P.P., R.M.E. and D.K.R. ; Methodology, P.P., D.K.R. and R.M.E. ; Software, S.J.A. ; Validation, S.O. and R.M.E. ; Formal analysis, P.P. and R.M.E. ; Investigation, P.P., D.K.R. and R.M.E. ; Resources, P.P. ; Data curation, P.A.K. and R.M.E. ; Writing--original draft preparation, D.K.R. ; Visualization, P.P., D.K.R., H.M.H. and R.M.E. ; Supervision, P.A.K. and D.K.R. ; Project administration, P.P., P.A.K., S.J.A. and S.O. ; Writing--review and editing, U.S., R.M.E. and N.D.; Funding acquisition, N.D. All authors have read and agreed to the published version of the manuscript.