Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast
This paper proposes a stochastic unit commitment (SUC) approach to solve a day-ahead unit commitment (UC) problem in a system with high uncertainty net load which is caused by photovoltaic (PV) power plants. In contrast with robust unit commitment (RUC) which only considers the worst-case scenario,...
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| Format: | Article |
| Language: | English |
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Universitas Gadjah Mada
2023-02-01
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| Series: | Jurnal Nasional Teknik Elektro dan Teknologi Informasi |
| Subjects: | |
| Online Access: | https://jurnal.ugm.ac.id/v3/JNTETI/article/view/5281 |
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| author | Muhammad Yasirroni Lesnanto Multa Putranto Sarjiya Husni Rois Ali Indra Triwibowo Qiangqiang Xie |
| author_facet | Muhammad Yasirroni Lesnanto Multa Putranto Sarjiya Husni Rois Ali Indra Triwibowo Qiangqiang Xie |
| author_sort | Muhammad Yasirroni |
| collection | DOAJ |
| description | This paper proposes a stochastic unit commitment (SUC) approach to solve a day-ahead unit commitment (UC) problem in a system with high uncertainty net load which is caused by photovoltaic (PV) power plants. In contrast with robust unit commitment (RUC) which only considers the worst-case scenario, SUC considers every possible scenario with its probability. Multiple possible PV curves were obtained using k-means clustering on historical data. The proportion of cluster members was used as a weight factor representing the occurrence probability of PV curves. The test was separated into two-step tests, namely day-ahead and real-time markets, using IEEE 10 generating unit system and solved using CPLEX. The results showed that in a day-ahead UC, SUC ($539,896) had lower cost than RUC ($548,005). However, when the total energy generated was considered, the SUC (20.78 $/MWh) cost higher compared to RUC (20.75 $/MWh). It is because the solution proposed by SUC is as robust as the RUC, but the generation cost formulation also considers over-commitment. Thus, SUC produced a fairer price for the independent power producer and electric utility in the day-ahead calculation. The results also showed that in the test environment of the real-time market, SUC was able to produce a robust solution without going into over-commitment. It is clearly shown in a 30 units system test with 10 centroids, in which SUC had a cheaper solution (20.7253 $/MWh) compared to RUC (20.7285 $/MWh), without violating power balance or going to load shedding. |
| first_indexed | 2024-04-10T05:33:39Z |
| format | Article |
| id | doaj.art-9f5500ace7c24a7b9c00881a15596c0d |
| institution | Directory Open Access Journal |
| issn | 2301-4156 2460-5719 |
| language | English |
| last_indexed | 2024-04-10T05:33:39Z |
| publishDate | 2023-02-01 |
| publisher | Universitas Gadjah Mada |
| record_format | Article |
| series | Jurnal Nasional Teknik Elektro dan Teknologi Informasi |
| spelling | doaj.art-9f5500ace7c24a7b9c00881a15596c0d2023-03-07T02:41:07ZengUniversitas Gadjah MadaJurnal Nasional Teknik Elektro dan Teknologi Informasi2301-41562460-57192023-02-01121566310.22146/jnteti.v12i1.52815281Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic ForecastMuhammad Yasirroni0Lesnanto Multa Putranto1Sarjiya2Husni Rois Ali3Indra Triwibowo4Qiangqiang Xie5Universitas Gadjah MadaUniversitas Gadjah MadaUniversitas Gadjah MadaUniversitas Gadjah MadaUniversitas Gadjah MadaHangzhou Dianzi UniversityThis paper proposes a stochastic unit commitment (SUC) approach to solve a day-ahead unit commitment (UC) problem in a system with high uncertainty net load which is caused by photovoltaic (PV) power plants. In contrast with robust unit commitment (RUC) which only considers the worst-case scenario, SUC considers every possible scenario with its probability. Multiple possible PV curves were obtained using k-means clustering on historical data. The proportion of cluster members was used as a weight factor representing the occurrence probability of PV curves. The test was separated into two-step tests, namely day-ahead and real-time markets, using IEEE 10 generating unit system and solved using CPLEX. The results showed that in a day-ahead UC, SUC ($539,896) had lower cost than RUC ($548,005). However, when the total energy generated was considered, the SUC (20.78 $/MWh) cost higher compared to RUC (20.75 $/MWh). It is because the solution proposed by SUC is as robust as the RUC, but the generation cost formulation also considers over-commitment. Thus, SUC produced a fairer price for the independent power producer and electric utility in the day-ahead calculation. The results also showed that in the test environment of the real-time market, SUC was able to produce a robust solution without going into over-commitment. It is clearly shown in a 30 units system test with 10 centroids, in which SUC had a cheaper solution (20.7253 $/MWh) compared to RUC (20.7285 $/MWh), without violating power balance or going to load shedding.https://jurnal.ugm.ac.id/v3/JNTETI/article/view/5281intermittencyk-meansmixed-integer linear programmingstochastic unit commitment |
| spellingShingle | Muhammad Yasirroni Lesnanto Multa Putranto Sarjiya Husni Rois Ali Indra Triwibowo Qiangqiang Xie Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast Jurnal Nasional Teknik Elektro dan Teknologi Informasi intermittency k-means mixed-integer linear programming stochastic unit commitment |
| title | Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast |
| title_full | Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast |
| title_fullStr | Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast |
| title_full_unstemmed | Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast |
| title_short | Stochastic Unit Commitment in Various System Sizes under High Uncertainty Photovoltaic Forecast |
| title_sort | stochastic unit commitment in various system sizes under high uncertainty photovoltaic forecast |
| topic | intermittency k-means mixed-integer linear programming stochastic unit commitment |
| url | https://jurnal.ugm.ac.id/v3/JNTETI/article/view/5281 |
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