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Optimal Scheduling of Grid Connected Solar Photovoltaic and Battery Storage System Considering Degradation Cost of Battery


The major objectives of this paper are to optimize the scheduling of solar photovoltaic (SPV) and battery energy storage systems (BESS) with the grid in order to reduce power loss and improve reliability. An unbalanced 8-bus rural distribution network in the village of Jalalabad, in the district of Ghaziabad, Uttar Pradesh, India, is under consideration. The main issue in village-based rural communities is excessive power outages and restricted grid power supplies. A modified artificial bee colony optimization technique has been used to identify optimum sizing, location, and timing in order to minimize the system's total cost and losses in order to overcome the aforementioned challenge. The management resource and demand response strategy are used to manage the load demand profile. The Coulomb Counting method is used to improve the estimation accuracy of the battery. The various results demonstrate the efficacy of the suggested method for determining appropriate PV, BESS, and grid size, location, and timing. In this work, only summer season is considered for SPV generation. In addition, the degradation cost of the battery and the excess power production have also been analyzed in this paper. It is evident that with the increase in the non-essential load shifting fraction βNELS from 0 to 25%, the fraction of excess power production decreases from 9.15 to 6.21%. The results demonstrate that combining solar PV with a rural network reduces carbon dioxide (CO2) emissions while also providing power 24 h a day, seven days a week.

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Solar radiation


Non-essential load


Change in non-essential load

C(BDC) :

Battery degradation cost

dB (Δt):

Depth of discharge of battery

LB (dB):

Life time of the battery

EBA (t):

Actual capacity of battery at time ‘t’

ηBC& ηBD :

Charging and discharging efficiency of battery

Emin :

Minimum energy rating of the battery

CO :

Total capital and operation cost of the battery

\({\mathrm{C}}_{\mathrm{n}}^{\mathrm{BESS}}\) :

Energy cost of the battery

\({\mathrm{C}}_{\mathrm{n}}^{\mathrm{PV}}\) :

Cost of solar PV

\({\mathrm{P}}_{\mathrm{n},\mathrm{ t}}^{\mathrm{PV}}\) :

Power from solar PV

\({\mathrm{P}}_{\mathrm{n},\mathrm{ t}}^{\mathrm{BESS}}\) :

Power from BESS

\({\mathrm{P}}_{\mathrm{ t}}^{\mathrm{gr}}\) :

Power from grid

C (0):

Initial charge of battery


Final charge of battery

CS :

Desired charge of battery

Cgr :

Cost of grid supply

Se :

Battery price ($/kwh)

SP :

Solar pv price ($/kWp)

Lo :

Losses of the objective system


Colony size

CB :

Battery replacement cost


Battery charging time

Pt :

Battery power

ΩT :

Set containing values of time


The fraction of non-essential load shifting


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Correspondence to Jitendra Kumar.

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Kumar, J., Kumar, N. Optimal Scheduling of Grid Connected Solar Photovoltaic and Battery Storage System Considering Degradation Cost of Battery. Iran J Sci Technol Trans Electr Eng (2022).

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  • Solar photovoltaic
  • Battery degradation cost
  • Optimization algorithm
  • Demand response
  • Power loss