Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals

Wind power intervals with different confidence levels have an impact on both the economic cost and risk of dispatch plans for power systems with wind power integration. The higher the confidence level, the greater the bandwidth of corresponding intervals. Thus, more reserves are needed, resulting in...

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Main Authors: Mengyue Hu, Zhijian Hu
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Energies
Subjects:
Online Access:http://www.mdpi.com/1996-1073/11/7/1710
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spelling doaj-95c4543c95fd4ea7959126fcba337fa22020-11-24T21:18:57ZengMDPI AGEnergies1996-10732018-07-01117171010.3390/en11071710en11071710Optimization Scheduling Method for Power Systems Considering Optimal Wind Power IntervalsMengyue Hu0Zhijian Hu1School of Electrical Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electrical Engineering, Wuhan University, Wuhan 430072, ChinaWind power intervals with different confidence levels have an impact on both the economic cost and risk of dispatch plans for power systems with wind power integration. The higher the confidence level, the greater the bandwidth of corresponding intervals. Thus, more reserves are needed, resulting in higher economic cost but less risk. In order to balance the economic cost and risk, a unit commitment model based on the optimal wind power confidence level is proposed. There are definite integral terms in the objective function of the model, and both the integrand function and integral upper/lower bound contain decision variables, which makes it difficult to solve this problem. The objective function is linearized and solved by discretizing the wind power probability density function and using auxiliary variables. On the basis, a rolling dispatching model considering the dynamic regulation costs among multiple rolling plans is established. In addition to balancing economic cost and risk, it can help to avoid repeated regulations among different rolling plans. Simulations are carried on a 10-units system and a 118-bus system to verify the effectiveness of the proposed models.http://www.mdpi.com/1996-1073/11/7/1710unit commitmentrolling dispatchwind power intervaloptimal confidence level
collection DOAJ
language English
format Article
sources DOAJ
author Mengyue Hu
Zhijian Hu
spellingShingle Mengyue Hu
Zhijian Hu
Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
Energies
unit commitment
rolling dispatch
wind power interval
optimal confidence level
author_facet Mengyue Hu
Zhijian Hu
author_sort Mengyue Hu
title Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
title_short Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
title_full Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
title_fullStr Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
title_full_unstemmed Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals
title_sort optimization scheduling method for power systems considering optimal wind power intervals
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-07-01
description Wind power intervals with different confidence levels have an impact on both the economic cost and risk of dispatch plans for power systems with wind power integration. The higher the confidence level, the greater the bandwidth of corresponding intervals. Thus, more reserves are needed, resulting in higher economic cost but less risk. In order to balance the economic cost and risk, a unit commitment model based on the optimal wind power confidence level is proposed. There are definite integral terms in the objective function of the model, and both the integrand function and integral upper/lower bound contain decision variables, which makes it difficult to solve this problem. The objective function is linearized and solved by discretizing the wind power probability density function and using auxiliary variables. On the basis, a rolling dispatching model considering the dynamic regulation costs among multiple rolling plans is established. In addition to balancing economic cost and risk, it can help to avoid repeated regulations among different rolling plans. Simulations are carried on a 10-units system and a 118-bus system to verify the effectiveness of the proposed models.
topic unit commitment
rolling dispatch
wind power interval
optimal confidence level
url http://www.mdpi.com/1996-1073/11/7/1710
work_keys_str_mv AT mengyuehu optimizationschedulingmethodforpowersystemsconsideringoptimalwindpowerintervals
AT zhijianhu optimizationschedulingmethodforpowersystemsconsideringoptimalwindpowerintervals
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