Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services
Distributed generators providing auxiliary service are an important means of guaranteeing the safe and economic operation of a distribution system. In this paper, considering an energy storage system (ESS), switchable capacitor reactor (SCR), step voltage regulator (SVR), and a static VAR compensato...
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doaj-4af2b2bc85624727aabc5d744b456a802021-08-26T13:42:44ZengMDPI AGEnergies1996-10732021-08-01144911491110.3390/en14164911Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary ServicesJian Zhang0Mingjian Cui1Yigang He2School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, ChinaDepartment of Electrical Engineering and Computer Science,The University of Tennessee,Knoxville, TN 37996, USASchool of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, ChinaDistributed generators providing auxiliary service are an important means of guaranteeing the safe and economic operation of a distribution system. In this paper, considering an energy storage system (ESS), switchable capacitor reactor (SCR), step voltage regulator (SVR), and a static VAR compensator (SVC), a two-stage multi-period hybrid integer second-order cone programming (SOCP) robust model with partial DGs providing auxiliary service is developed. If the conic relaxation is not exact, a sequential SOCP is formulated using convex–concave procedure (CCP) and cuts, which can be quickly solved. Moreover, the exact solution of the original problem can be recovered. Furthermore, in view of the shortcomings of the large computer storage capacity and slow computational rate for the column and constraint generation (CCG) method, a method direct iteratively solving the master and sub-problem is proposed. Increases to variables and constraints to solve the master problem are not needed. For the sub-problem, only the model of each single time period needs to be solved. Then, their objective function values are accumulated, and the worst scenarios of each time period are concatenated. As an outcome, a large amount of storage memory is saved and the computational efficiency is greatly enhanced. The capability of the proposed method is validated with three simulation cases.https://www.mdpi.com/1996-1073/14/16/4911ancillary servicesCCPdistribution systemrobust optimizationsequential SOCP |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jian Zhang Mingjian Cui Yigang He |
spellingShingle |
Jian Zhang Mingjian Cui Yigang He Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services Energies ancillary services CCP distribution system robust optimization sequential SOCP |
author_facet |
Jian Zhang Mingjian Cui Yigang He |
author_sort |
Jian Zhang |
title |
Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services |
title_short |
Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services |
title_full |
Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services |
title_fullStr |
Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services |
title_full_unstemmed |
Multi-Period Fast Robust Optimization for Partial Distributed Generators (DGs) Providing Ancillary Services |
title_sort |
multi-period fast robust optimization for partial distributed generators (dgs) providing ancillary services |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2021-08-01 |
description |
Distributed generators providing auxiliary service are an important means of guaranteeing the safe and economic operation of a distribution system. In this paper, considering an energy storage system (ESS), switchable capacitor reactor (SCR), step voltage regulator (SVR), and a static VAR compensator (SVC), a two-stage multi-period hybrid integer second-order cone programming (SOCP) robust model with partial DGs providing auxiliary service is developed. If the conic relaxation is not exact, a sequential SOCP is formulated using convex–concave procedure (CCP) and cuts, which can be quickly solved. Moreover, the exact solution of the original problem can be recovered. Furthermore, in view of the shortcomings of the large computer storage capacity and slow computational rate for the column and constraint generation (CCG) method, a method direct iteratively solving the master and sub-problem is proposed. Increases to variables and constraints to solve the master problem are not needed. For the sub-problem, only the model of each single time period needs to be solved. Then, their objective function values are accumulated, and the worst scenarios of each time period are concatenated. As an outcome, a large amount of storage memory is saved and the computational efficiency is greatly enhanced. The capability of the proposed method is validated with three simulation cases. |
topic |
ancillary services CCP distribution system robust optimization sequential SOCP |
url |
https://www.mdpi.com/1996-1073/14/16/4911 |
work_keys_str_mv |
AT jianzhang multiperiodfastrobustoptimizationforpartialdistributedgeneratorsdgsprovidingancillaryservices AT mingjiancui multiperiodfastrobustoptimizationforpartialdistributedgeneratorsdgsprovidingancillaryservices AT yiganghe multiperiodfastrobustoptimizationforpartialdistributedgeneratorsdgsprovidingancillaryservices |
_version_ |
1721193773606633472 |