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Optimized scheduling for electric lift trucks in a sugarcane agro-industry based on thermal, biomass and solar resources

Original Paper
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Abstract

Resource scheduling for both cost and pollution minimization in the power system is so crucial. To reduce the greenhouse gas emission, employing renewable energy resources, especially solar and wind energy, and beside them plug-in hybrid electric vehicles are effective solutions. In industrial factories, using biomass resources for power generation is both economic and environmental approach. In sugarcane company, bagasse is plant fiber residue which is used as fuel. Electric lift trucks, capable of being connected to power grid, could decrease the pollution in industrial transportations. In this paper, scheduling problem for a large-scale sugarcane factory including solar resources, a thermal unit, and electric lift trucks is presented and solved by CPLEX solver in GAMS software. In order to consider uncertainties, different scenarios are noticed. To contribute better understanding of optimization problem, cost, pollution, and charging regime of electric lift trucks are carefully analyzed. The results show that implementation of the biomass electric power generation is effective for reducing cost and amount of emission.

Keywords

Sugarcane Renewable energy Biomass Plug-in electric lift trucks Resource scheduling Cost Pollution 

List of symbols

\(\psi_{\hbox{min} } /\psi_{\hbox{max} }\)

Min/max. State of charge

\(I_{i} \left( t \right)\)

Status of unit i at hour t

\(I_{\text{ch}} \left( t \right)\)

Charging status of lift trucks at time t (if \(I_{\text{ch}} \left( t \right) = 1\), then lift trucks are in charge mode)

Idch(t)

Discharging status of lift trucks at time t (if it equals to one, lift trucks are in discharge mode)

\(N_{\text{LF}} \left( t \right)\)

Number of electric lift trucks connected to the grid at time t

n

Number of all electric vehicles in investigated place

αi, βi, γi

Emission coefficients of unit i

ai, bi, ci

Cost coefficients of unit i

I

If it equals to one, the unit is thermal power plant and if it equals to two, the unit is biomass resource

H

Scheduling hours

S

Sets of scenario

η

Efficiency of batteries

wc

Weight factor for cost

we

Weight factor for emission

\({\text{fc}}_{i} ()\)

Fuel cost function of unit i

\({\text{Sc}}_{i} ()\)

Start-up cost function of unit i

\({\text{fe}}_{i} ()\)

Emission function of unit i

D(t)

Load demand at time t

pfei

Emission penalty factor of unit i

Psolars(t)

Power of solar farm at time t considering scenario s

PLF

Capacity of the electric lift truck’s batteries

PLFs(t)

Power of the electric lift trucks at time t considering scenario s

R

Efficiency of the battery

\(E^{S} \left( t \right)\)

Total energy of all batteries at time t considering scenario s

\(E_{\text{F}}\)

Energy of battery at final hour of day

\(E_{0}\)

Primary energy of battery at starting time for scheduling

\(E_{\hbox{min} } ,E_{\hbox{max} }\)

Maximum and minimum energy of battery

Pchs(t)

Charging power of all plug-in lift trucks at time t considering scenario s

\(P_{\text{dch}}^{s} \left( t \right)\)

Discharging power of all plug-in lift trucks at time t considering scenario s

\(i1_{\text{ch}} \left( t \right), i1_{\text{dch}} \left( t \right)\)

Status of charging and discharging plug-in lift trucks

Randn

A random number between 0 and 1 in normal probability distributed curve

Pis(t)

Power of unit i at time t considering scenario s

Pimax, Pimin

Max/min output limit of unit i

ppv

Output power of solar panel

ppv-r

Rated output power of PV array

Fpv

De-rating factor considering shading, wiring, etc.

G

Solar radiation in current time

Gstc

Solar radiation under the standard test condition

αT

Temperature coefficient of power

Tstc

Temperature on PV cells under standard test condition

Notes

Acknowledgements

The authors would like to thank Dr. Babak Mozafari, the dean of Electrical and computer faculty of science and research branch Islamic Azad University, for supporting this research.

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Copyright information

© Islamic Azad University (IAU) 2017

Authors and Affiliations

  1. 1.Department of Electrical Engineering, Faculty of Electrical and Computer, Science and Research BranchIslamic Azad UniversityTehranIran

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