I want to implement a battery system for a renewable plant of energy who feeds a machine. For example, The machine requires 1000 kw/h or the energy closest to that amount. If the energy generated exceeds 1000 kw/h, the surplus could be used to charge the battery, which, let’s say, is 100 kw. If the energy produced is less than 1000 kw/h and there is energy in the battery, the energy from the battery should be used to power the machine. An example generated energy dataset could be the following:

data set energia

Where should I obtain a new energy and battery charge level data set as follows:

data set Bateria

New data set Energia

I am doing the simulation for-loop each of the hours in 1 year (8760) with a thousand possible paths of energy generation values. I am currently making a for for each column where I check the conditions (ther is more conditions), the code is the next:

carga_bateria<- data.frame(matrix(0, nrow = 1040, ncol = 8760))
for (i in 2:8760) {  
cond1<-energia[,i]>pot_elec
carga_bateria[cond1,i]=carga_bateria[cond1,i-1]*(1-0.02/100)+pmin(n_bat*7.55-carga_bateria[cond1,i-1]*(1-0.02/100),(energia[cond1,i]-pot_elec)*0.85)
# si la energia generada es mayor a la necsitada entonces la bateria queda con la carga anterior con la perdida de 0.02% + el minimo entre
#la bateria que hace falta y el excedente generado incluyendo la perdida de eficiencia al cargar de 85%.

cond2<-(energia[,i]+pmax(carga_bateria[,i-1]*(1-0.02/100)-n_bat*7.55*0.2,0))<pot_elec*0.3#cuando ni incluyendo la bateria en t-1 llega al 30% de la capacidad del electrolizador, entonces tambien se carga bateria
carga_bateria[cond2,i]=carga_bateria[cond2,i-1]*(1-0.02/100)+pmin(n_bat*7.55-carga_bateria[cond2,i-1]*(1-0.02/100),(energia[cond2,i])*0.85)

cond3<- pot_elec>energia[,i]&(pot_elec-energia[,i])<(carga_bateria[,i-1]*(1-0.02/100)-n_bat*7.55*0.2)#Caso desacarga parcial bateria, si el faltante lo puede cubrir la bateria
carga_bateria[cond3,i]=carga_bateria[cond3,i-1]*(1-0.02/100)-(pot_elec-energia[cond3,i]) #la bateria se descargaga en ese faltante
energia[cond3,i]<- pot_elec #la energia llega a la capacidad

cond4<- (energia[,i]+pmax(carga_bateria[,i-1]*(1-0.02/100)-n_bat*7.55*0.2,0))>pot_elec*0.3&(energia[,i]+pmax(carga_bateria[,i-1]*(1-0.02/100)-n_bat*7.55*0.2,0))<pot_elec# caso de descarga total
carga_bateria[cond4,i]= n_bat*7.55*0.2#la bateria se descargaga totalmente
energia[cond4,i]<- energia[cond4,i]+(carga_bateria[cond4,i-1]*(1-0.02/100)-n_bat*7.55*0.2) #la energia llega a la capacidad


cond99<-!cond1&!cond2&!cond3&!cond4
carga_bateria[cond99,i]=carga_bateria[cond99,i-1]*(1-0.02/100)
validacion[1,i]<-sum(cond1);validacion[2,i]<-sum(cond2);validacion[3,i]<-sum(cond3);validacion[4,i]<-sum(cond4)
validacion[5,i]<- sum(cond1,cond2,cond3,cond4)

}

but I want to make the process as efficient as possible. I would believe that parallelization is not an option since the analysis is sequential and conditional, although I don’t know.