Profit‐based unit commitment with security constraints and fair allocation of cost saving in industrial microgrids

Derakhshandeh, Sayed Yaser; Golshan, Mohammad; Masoum, Mohammad A. S.

doi:10.1049/iet-smt.2013.0044

Cited by 28 publications

(21 citation statements)

References 30 publications

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“…Industrial microgrids are based on the corporation among a number of factories that use DERs to supply their electric loads while the require heat for the production processes is obtained from the boilers or CHP systems. Industrial microgrids can trade electricity from the upstream network while only the neighboring factories usually cooperate to procure their thermal requirements …”

Section: Industrial Microgridsmentioning

confidence: 99%

“…Among various types of CHP systems, gas turbines (GTs), natural gas engines (NGs), and micro turbines (MTs) play major roles in IMGs. These types of CHP systems have linear constraints and cost functions . However, beside these types of generators, small steam turbine (ST) generators with nonlinear constraint and cost functions are also used in IMGs.…”

Section: Linear Model Representation Of Nonlinear Generation Unitsmentioning

confidence: 99%

“…The main inspirations for selecting the scenario‐based method for solving stochastic programming in IMGs are Industrial microgrids are not very large scale systems, hence using the scenario‐based method will not significantly increase the required optimization calculation time. Many IMG's constraints are linear while the remaining nonlinear constraints can be changed to linear forms. In this view, the presence of nonlinear constraints will not have significant impacts on time of calculations. …”

Section: Problem Formulationmentioning

confidence: 99%

“…Cost of electricity production by GTs, NGs, and MTs is modeled as linear functions while the uncertainties related to the efficiency have also been considered. These types of CHP systems have no startup and shutdown costs . Heat production cost of boilers and operation/maintenance cost of PV panels are formulated as linear functions:

{Cost}_{i, h}^{b, s} = \frac{b_{i, h}^{s}}{η_{i}^{b}} * italicgp,

{Cost}_{i, h}^{italicPV, s} = {P_{i, h}^{PV, s}}^{*} {OM}_{i}^{PV} .

…”

Section: Problem Formulationmentioning

confidence: 99%

“…Maximum available reserve from each steam turbine CHP system is

{\overset{true-}{P}}_{i, h} - P_{i, h}^{m}

while for GTs, NGs, and MTs, it can be stated as

P_{{italicmax}_{i}} - P_{i, h}^{m} .

Connecting line capacity …”

Section: Problem Formulationmentioning

confidence: 99%

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Stochastic scenario-based generation scheduling in industrial microgrids

Derakhshandeh

Golshan

Ghazizadeh

et al. 2017

Int Trans Electr Energ Syst

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Summary Industrial parks are forming industrial microgrids (IMGs) with factories, distributed energy resources, electric loads, heat loads, and combined heat and power systems as well as renewable distributed energy resources and plug‐in electric vehicles (PEVs). Generation scheduling (GS) in IMGs is affected by the stochastic behavior of electric and heat loads due to outages of production processes or production lines and the uncertainties in solar irradiance and combined heat and power systems. This paper presents a stochastic scenario‐based GS framework to consider uncertainties in an IMG coordinated with PEV charging. Although the scenario‐based methods are usually very time consuming, this paper shows that their applications in IMGs will not significantly increase the calculation time. The proposed formulation guaranties that occurrence of each condition of uncertainty will not affect the PEV activities. An IMG with 12 factories, photovoltaic generations, and 6 types of electric vehicles with different battery sizes is considered and simulated. The main contributions are (1) a new stochastic GS problem formulation to minimize the cost of IMGs while fully charging all PEVs within their requested periods considering the network security, factories, and PEV constraints; (2) changing the nonlinear constraints to linear forms suitable for scenario‐based optimization; and (3) considering the stochastic behavior of electric loads without requiring any data about their internal process in each factory.

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Section: Industrial Microgridsmentioning

confidence: 99%

Section: Linear Model Representation Of Nonlinear Generation Unitsmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

{Cost}_{i, h}^{b, s} = \frac{b_{i, h}^{s}}{η_{i}^{b}} * italicgp,

{Cost}_{i, h}^{italicPV, s} = {P_{i, h}^{PV, s}}^{*} {OM}_{i}^{PV} .

…”

Section: Problem Formulationmentioning

confidence: 99%

“…Maximum available reserve from each steam turbine CHP system is

{\overset{true-}{P}}_{i, h} - P_{i, h}^{m}

while for GTs, NGs, and MTs, it can be stated as

P_{{italicmax}_{i}} - P_{i, h}^{m} .

Connecting line capacity …”

Section: Problem Formulationmentioning

confidence: 99%

See 3 more Smart Citations

Stochastic scenario-based generation scheduling in industrial microgrids

Derakhshandeh

Golshan

Ghazizadeh

et al. 2017

Int Trans Electr Energ Syst

Self Cite

View full text Add to dashboard Cite

show abstract

Unit commitment in industrial microgrids with plug-in electric vehicles and photovoltaic generation

Derakhshandeh

Masoum

Golshan

2014

Int. Trans. Electr. Energ. Syst.

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Summary Industrial microgrids (IMGs) consist of factories with distributed energy resources (DERs) and electric loads that heavily rely on combined heat and power (CHP) systems. The new generations of IMGs are expected to also include renewable DERs and plug‐in electric vehicles (PEVs) with different power ratings and charging characteristics. This paper proposes a profit‐based security constrained unit commitment (PB‐SCUC) formulation for IMGs with PEV charging and renewable DERs that includes both microgrid security and factories constraints as well as the PEV charging requirements. PB‐SCUC will utilize the generators waste heat to fulfill thermal requirements and also consider the status of renewable DERs to decrease the overall cost of IMG. To demonstrate the effectiveness of PB‐SCUC, detailed simulation results are presented and analyzed for an IMG consisting of 12 factories and 6 types of PEVs without/with photovoltaic generations operating in grid‐connected and stand‐alone modes. Copyright © 2014 John Wiley & Sons, Ltd.

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