Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation
This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is use...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9126773/ |
| _version_ | 1819158662717898752 |
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| author | Mohammad Amin Mirzaei Mohammad Hemmati Kazem Zare Behnam Mohammadi-Ivatloo Mehdi Abapour Mousa Marzband Ali Farzamnia |
| author_facet | Mohammad Amin Mirzaei Mohammad Hemmati Kazem Zare Behnam Mohammadi-Ivatloo Mehdi Abapour Mousa Marzband Ali Farzamnia |
| author_sort | Mohammad Amin Mirzaei |
| collection | DOAJ |
| description | This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in real-time. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost. |
| first_indexed | 2024-12-22T16:28:14Z |
| format | Article |
| id | doaj.art-5fd35a8d68ab425091dff95d8ba3729d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T16:28:14Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5fd35a8d68ab425091dff95d8ba3729d2022-12-21T18:20:07ZengIEEEIEEE Access2169-35362020-01-01812178012179410.1109/ACCESS.2020.30052949126773Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail TransportationMohammad Amin Mirzaei0https://orcid.org/0000-0002-8793-7642Mohammad Hemmati1Kazem Zare2https://orcid.org/0000-0003-4729-1741Behnam Mohammadi-Ivatloo3Mehdi Abapour4https://orcid.org/0000-0003-0241-7021Mousa Marzband5Ali Farzamnia6https://orcid.org/0000-0001-8618-7256Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranDepartment of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne, U.K.Faculty of Engineering, Universiti Malaysia Sabah, Kota Kinabalu, MalaysiaThis paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in real-time. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost.https://ieeexplore.ieee.org/document/9126773/Battery-based energy storage transportdemand side-managementrail transport networkday-ahead market clearinghybrid optimization techniquewind energy |
| spellingShingle | Mohammad Amin Mirzaei Mohammad Hemmati Kazem Zare Behnam Mohammadi-Ivatloo Mehdi Abapour Mousa Marzband Ali Farzamnia Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation IEEE Access Battery-based energy storage transport demand side-management rail transport network day-ahead market clearing hybrid optimization technique wind energy |
| title | Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation |
| title_full | Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation |
| title_fullStr | Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation |
| title_full_unstemmed | Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation |
| title_short | Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation |
| title_sort | two stage robust stochastic electricity market clearing considering mobile energy storage in rail transportation |
| topic | Battery-based energy storage transport demand side-management rail transport network day-ahead market clearing hybrid optimization technique wind energy |
| url | https://ieeexplore.ieee.org/document/9126773/ |
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