I have a bunch of solar panels, each one is connected to an inverter. For each solar panel I have two sensors, a wind and a west sensor. From every inverter, I collect the power output. The readings are collected for every 5 minutes, and I have a dataset over 7 days.
I know that the power can be estimated using the equation:
Here is what I did so far: I only used the west sensor as I thought the wind sensor has little effect on the power output of a solar panel(common sense?). Then, I grouped the data by hour and then day, for example, for on the 22.12.2022 I got 24 readings, and so on.
I rearranged the equation, to get something like Ax Bxy C = 0, see here:
A_e * irr_s A_e * eta_T * (irr_s * T_m irr_s * 25) - rho_A = 0
if I say, A = irr_s and B = irr_s * T_m irr_s * 25 and C = -rho_A,
Now I calculated the two unknowns, A_e and eta_T. I used matrixes to solve different pairs of equations using:
Let us assume the two pairs look like this:
A_1x B_1xy C_1 = 0 and
A_2x B_2xy C_2 = 0
M1 =
A_1, B_1
A_2, B_2
and
M2 =
C_1
C_2
ROOTS =
R_1
R_2
Then, ROOTS = np.linalg.inv(M1).dot(M2)
I plotted them on a graph, see below: Click here
Do you think my approach is good? How else could one approach this problem? Thank you for your inputs in advance!
CodePudding user response:
It is not linear equation.
ro = ae * irr * (1 eta * (t-25))
It is not clear what values change between measures. Let ro
, irr
and t
:
ro1 = ae * irr1 * (1 eta * (t1-25))
ro2 = ae * irr2 * (1 eta * (t2-25))
divide these equations
ro1/ro2 = irr1/irr2 *(1 eta * (t1-25)) / (1 eta * (t2-25))
ro1 * irr2*(1 eta * (t2-25)) = ro2 * irr1*(1 eta * (t1-25))
this is linear equation for eta
, we can easily solve it for eta
, then substitute eta
into the first equation to get ae
CodePudding user response:
From the little that I understand of your experiments, you are probably able to measure the temperature and the power. I would be surprised that you have access to irradiation.
If this is the case, you can't find any of the coefficients. Even worse if you don't record the temperatures.