Article(id=1156986630797091483, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403210, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1714406400000, receivedDateStr=2024-04-30, revisedDate=1735142400000, revisedDateStr=2024-12-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1753776708553, onlineDateStr=2025-07-29, pubDate=1742227200000, pubDateStr=2025-03-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753776708553, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753776708553, creator=13701087609, updateTime=1753776708553, updator=13701087609, issue=Issue{id=1156963927277003616, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='8', pageStart='3079', pageEnd='3528', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753771295613, creator=13701087609, updateTime=1753777038876, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1156988016305726153, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1156988016305726154, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3258, endPage=3267, ext={EN=ArticleExt(id=1156986632919409346, articleId=1156986630797091483, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Optimal Decommissioning Decisions for Aged Assets Taking into Account the Impact of Transmission and Distribution Tariffs, columnId=1156963928891806289, journalTitle=Science Technology and Engineering, columnName=Electrical Technology, runingTitle=null, highlight=null, articleAbstract=

Given the prevalent issue of aging assets within power grid companies and the subpar management of aging equipment, a decision-making approach was introduced for optimizing the decommissioning of aging assets, taking into account the influence of transmission and distribution tariffs. Firstly, in accordance with the policy framework for reforming transmission and distribution tariffs, an accounting model for transmission and distribution tariffs for provincial power grids operating at varying voltage levels was developed. Secondly, the decommissioning planning model for over-age assets was established with the optimization objective of achieving the highest return throughout the investment cycle. The decision variables of time and scale for decommissioning were utilized in this model. Through a process of rolling optimization and feedback correction, the model ensured that the scale of decommissioning for overage assets in each stage aligns with the desired value, thereby meeting the premise of system reliability. Finally, the efficacy of the model and its ability to enhance investment efficiency were demonstrated through the examination of the${110}\mathrm{{kV}}$voltage level grid in a specific province.

, correspAuthors=Wen-xia LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Hong-wei YU, Wen-xia LIU, Fu-xin WANG, Wan-tao HU, Tong LI, Xiao-hui WANG), CN=ArticleExt(id=1156986768659669424, articleId=1156986630797091483, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=计及输配电价影响的逾龄资产退役优化决策, columnId=1154013917111115781, journalTitle=科学技术与工程, columnName=电工技术, runingTitle=null, highlight=null, articleAbstract=

针对当前电网公司逾龄资产体系较大且逾龄设备管理相对薄弱的现状,提出一种考虑输配电价影响的逾龄资产退役优化决策方法。首先,根据输配电价改革的政策方案,建立省级电网在不同电压等级下的输配电价核算模型;其次,以全投资周期收益最高为优化目标、以逾龄资产退役时间和退役规模为决策变量,建立逾龄资产退役规划模型,并通过滚动优化和反馈矫正过程,确保在每个阶段逾龄资产退役规模能够跟踪期望值,以在满足系统可靠性的前提下尽可能使电网公司效益最大化;最后,以某省${110}\mathrm{\;{kV}}$电压等级电网为例验证了模型的有效性以及在提高投资效率方面的优越性。

, correspAuthors=刘文霞, authorNote=null, correspAuthorsNote=
*刘文霞(1967-),女,汉族,北京人,博士,教授。研究方向:电力系统规划与可靠性、电力系统风险评估。E-mail: liuwenxia001@163.com。
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禹红伟(1996—),男,回族,宁夏固原人,硕士研究生。研究方向:电网资产管理、可靠性评估。E-mail:17750966779@163.com。

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禹红伟(1996—),男,回族,宁夏固原人,硕士研究生。研究方向:电网资产管理、可靠性评估。E-mail:17750966779@163.com。

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禹红伟(1996—),男,回族,宁夏固原人,硕士研究生。研究方向:电网资产管理、可靠性评估。E-mail:17750966779@163.com。

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High Voltage Engineering, 2018. 44(11): 3751-3759., articleTitle=Optimization model of distribution network maintenance plan based on equipment status evaluation and power grid loss risk, refAbstract=null)], funds=[Fund(id=1156986786783257504, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, awardId=5100-202456030A-1-1-ZN, language=CN, fundingSource=国家电网公司总部科技项目(5100-202456030A-1-1-ZN), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1156986774179373598, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, xref=1, ext=[AuthorCompanyExt(id=1156986774183567903, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, companyId=1156986774179373598, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North 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articleId=1156986630797091483, companyId=1156986774254871074, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 国网经济技术研究院有限公司 北京 102200)])], figs=[ArticleFig(id=1156986785021649757, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 1, caption=Components of permitted income, figureFileSmall=DJl/Gpm6kx/ROPgFIhYqRQ==, figureFileBig=ZphbRlda+qg1cZappXvBKA==, tableContent=null), ArticleFig(id=1156986785067787104, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图1, caption=准许收入的组成, figureFileSmall=DJl/Gpm6kx/ROPgFIhYqRQ==, figureFileBig=ZphbRlda+qg1cZappXvBKA==, tableContent=null), ArticleFig(id=1156986785113924450, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 2, caption=Multi-stage optimization schematic, figureFileSmall=41th9OCq/gYiEAzffSorRw==, figureFileBig=osdnVjyvsLyvm6KVt9eXBA==, tableContent=null), ArticleFig(id=1156986785172644709, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图2, caption=多阶段优化示意, figureFileSmall=41th9OCq/gYiEAzffSorRw==, figureFileBig=osdnVjyvsLyvm6KVt9eXBA==, tableContent=null), ArticleFig(id=1156986785214587752, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 3, caption=The framework of rolling optimization model of over-aged assets technical reform based on multi-stage idea, figureFileSmall=WksrTRs8sK+71exkiBnI9Q==, figureFileBig=isSMGAy0XKj0Ep4O/aaUsw==, tableContent=null), ArticleFig(id=1156986785269113706, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图3, caption=基于多阶段思想的逾龄资产退役滚动优化模型框架, figureFileSmall=WksrTRs8sK+71exkiBnI9Q==, figureFileBig=isSMGAy0XKj0Ep4O/aaUsw==, tableContent=null), ArticleFig(id=1156986785323639661, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 4, caption=Solution process for rolling optimization strategy of technical transformation of overage assets, figureFileSmall=fcfgZRXuTluXUZxp+esXTw==, figureFileBig=m3tCh+PnmTUywvS2EmDsKA==, tableContent=null), ArticleFig(id=1156986785382359920, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图4, caption=逾龄资产技改滚动优化策略求解流程, figureFileSmall=fcfgZRXuTluXUZxp+esXTw==, figureFileBig=m3tCh+PnmTUywvS2EmDsKA==, tableContent=null), ArticleFig(id=1156986785428497266, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 5, caption=Technical transformation strategy for overage assets, figureFileSmall=ztQtXfO1tZW/aAe7lqySaA==, figureFileBig=GzbffyKXuFcjvQinhS638A==, tableContent=null), ArticleFig(id=1156986785478828917, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图5, caption=逾龄资产退役策略, figureFileSmall=ztQtXfO1tZW/aAe7lqySaA==, figureFileBig=GzbffyKXuFcjvQinhS638A==, tableContent=null), ArticleFig(id=1156986785529160567, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 6, caption=Trends in costs across regulatory cycles, figureFileSmall=8+i8dykkEzFebPhj28Azyg==, figureFileBig=tTJ0ui+wGfOJRAjC+aqizA==, tableContent=null), ArticleFig(id=1156986785575297913, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图6, caption=各监管周期成本变化趋势, figureFileSmall=8+i8dykkEzFebPhj28Azyg==, figureFileBig=tTJ0ui+wGfOJRAjC+aqizA==, tableContent=null), ArticleFig(id=1156986785621435260, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 7, caption=Differentiated decommissioning strategy for over-aged assets, figureFileSmall=lXaSBtwWKnLubhAFF7ec4g==, figureFileBig=7W9kK2aaWWV3ZGPOf0yKtA==, tableContent=null), ArticleFig(id=1156986785684349822, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图7, caption=逾龄资产差异化退役策略, figureFileSmall=lXaSBtwWKnLubhAFF7ec4g==, figureFileBig=7W9kK2aaWWV3ZGPOf0yKtA==, tableContent=null), ArticleFig(id=1156986785751458687, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Fig. 8, caption=Comparative analysis of the scale of over-age assets technical reform, figureFileSmall=9Xw68wLsyCBF7ezJwVDDew==, figureFileBig=zUuKW0hnikT2Pt+5PeFjxw==, tableContent=null), ArticleFig(id=1156986785805984640, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=图8, caption=逾龄资产技改规模对比分析, figureFileSmall=9Xw68wLsyCBF7ezJwVDDew==, figureFileBig=zUuKW0hnikT2Pt+5PeFjxw==, tableContent=null), ArticleFig(id=1156986785860510595, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Table 1, caption=Reliability parameters of transformer, figureFileSmall=null, figureFileBig=null, tableContent=
可靠性参数 故障率
早期失效期 ${\lambda }_{1}$ 0.1050
随机失效期 ${\lambda }_{2}$ 0.006 0
损耗失效期 ${\lambda }_{3}$ 0.065 8
), ArticleFig(id=1156986785919230852, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=表1, caption=变压器可靠性参数, figureFileSmall=null, figureFileBig=null, tableContent=
可靠性参数 故障率
早期失效期 ${\lambda }_{1}$ 0.1050
随机失效期 ${\lambda }_{2}$ 0.006 0
损耗失效期 ${\lambda }_{3}$ 0.065 8
), ArticleFig(id=1156986785977951112, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Table 2, caption=2019-2022 basic operation data of a provincial ${110}\mathrm{{kV}}$ power grid at the end of the regulatory cycle, figureFileSmall=null, figureFileBig=null, tableContent=
指标 数值
售电量/(MW·h) 643.387
固定资产原值/亿元 396.47
逾龄资产值/亿元 75.58
逾龄变压器资产原值/亿元 19.33
基期有效资产/亿元 117.52
基期准许成本/亿元 103.77
累计折旧/亿元 174.94
输配电价 $/\left\lbrack {\text{元}\cdot {\left(\mathrm{{kW}}\cdot \mathrm{h}\right)}^{-1}}\right\rbrack$ 0.1701
), ArticleFig(id=1156986786032477067, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=表2, caption=2019-2022 年监管周期末某省级${110}\mathrm{{kV}}$ 电网运行基础数据, figureFileSmall=null, figureFileBig=null, tableContent=
指标 数值
售电量/(MW·h) 643.387
固定资产原值/亿元 396.47
逾龄资产值/亿元 75.58
逾龄变压器资产原值/亿元 19.33
基期有效资产/亿元 117.52
基期准许成本/亿元 103.77
累计折旧/亿元 174.94
输配电价 $/\left\lbrack {\text{元}\cdot {\left(\mathrm{{kW}}\cdot \mathrm{h}\right)}^{-1}}\right\rbrack$ 0.1701
), ArticleFig(id=1156986786091197326, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Table 3, caption=Optimization model parameters for the retirement scale of overaged assets in a provincial${110}\mathrm{{kV}}$ power grid during the regulatory period from 2023 to 2038, figureFileSmall=null, figureFileBig=null, tableContent=
指标 数值 指标 数值
供电可靠性目标 $/\%$ 99.883 7 缺电损失评价系数/[元 $\cdot {\left(\mathrm{{kW}}\cdot \mathrm{h}\right)}^{-1}$] 5
财务折旧率/% 5 所得稅稅率/% 25
材料费率 $/\%$ 0.5 资产负债率/% 67.61
修理费率 $/\%$ 0.5 债务资本成本/% 4.8
人工费率/% 1 输电损耗率/% 5
其他运营费率/% 2.5 折旧年限/年 15
), ArticleFig(id=1156986786154111889, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=表3, caption=2023-2038 年监管周期内某省级 110 kV 电网逾龄资产退役规模优化模型参数, figureFileSmall=null, figureFileBig=null, tableContent=
指标 数值 指标 数值
供电可靠性目标 $/\%$ 99.883 7 缺电损失评价系数/[元 $\cdot {\left(\mathrm{{kW}}\cdot \mathrm{h}\right)}^{-1}$] 5
财务折旧率/% 5 所得稅稅率/% 25
材料费率 $/\%$ 0.5 资产负债率/% 67.61
修理费率 $/\%$ 0.5 债务资本成本/% 4.8
人工费率/% 1 输电损耗率/% 5
其他运营费率/% 2.5 折旧年限/年 15
), ArticleFig(id=1156986786217026451, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Table 4, caption=Costs and benefits at each stage, figureFileSmall=null, figureFileBig=null, tableContent=
监管周期 售电收益/亿元 成本/亿元 最终收益/亿元
1 312.22 121.91 190.31
2 312.88 115.37 197.52
3 312.61 93.25 219.36
4 312.45 127.38 185.07
5 313.14 113.09 200.05
), ArticleFig(id=1156986786300912533, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=表4, caption=各监管周期成本及收益, figureFileSmall=null, figureFileBig=null, tableContent=
监管周期 售电收益/亿元 成本/亿元 最终收益/亿元
1 312.22 121.91 190.31
2 312.88 115.37 197.52
3 312.61 93.25 219.36
4 312.45 127.38 185.07
5 313.14 113.09 200.05
), ArticleFig(id=1156986786368021399, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=EN, label=Table 5, caption=Comparison of results of different schemes, figureFileSmall=null, figureFileBig=null, tableContent=
方案 方案 1 方案 2
退役规模/亿元 90.14 61.20
电网逾龄资产规模/亿元 7.15 36.08
售电收入/亿元 1 563.30 1 569.60
成本/亿元 570.99 966.17
最终收益/亿元 992.31 603.43
), ArticleFig(id=1156986786422547353, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986630797091483, language=CN, label=表5, caption=不同方案结果对比, figureFileSmall=null, figureFileBig=null, tableContent=
方案 方案 1 方案 2
退役规模/亿元 90.14 61.20
电网逾龄资产规模/亿元 7.15 36.08
售电收入/亿元 1 563.30 1 569.60
成本/亿元 570.99 966.17
最终收益/亿元 992.31 603.43
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计及输配电价影响的逾龄资产退役优化决策
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禹红伟 1 , 刘文霞 1, * , 王馥馨 1 , 胡皖涛 1 , 李瞳 2 , 王晓晖 2
科学技术与工程 | 电工技术 2025,25(8): 3258-3267
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科学技术与工程 | 电工技术 2025, 25(8): 3258-3267
计及输配电价影响的逾龄资产退役优化决策
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禹红伟1 , 刘文霞1, * , 王馥馨1, 胡皖涛1, 李瞳2, 王晓晖2
作者信息
  • 1 新能源电力系统国家重点实验室 北京 102206
  • 2 国网经济技术研究院有限公司 北京 102200
  • 禹红伟(1996—),男,回族,宁夏固原人,硕士研究生。研究方向:电网资产管理、可靠性评估。E-mail:17750966779@163.com。

通讯作者:

*刘文霞(1967-),女,汉族,北京人,博士,教授。研究方向:电力系统规划与可靠性、电力系统风险评估。E-mail: liuwenxia001@163.com。
Optimal Decommissioning Decisions for Aged Assets Taking into Account the Impact of Transmission and Distribution Tariffs
Hong-wei YU1 , Wen-xia LIU1, * , Fu-xin WANG1, Wan-tao HU1, Tong LI2, Xiao-hui WANG2
Affiliations
  • 1 State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University) Beijing 102206 China
  • 2 State Grid Economics and Technology Research Institute Limited Beijing 102200 China
出版时间: 2025-03-18 doi: 10.12404/j.issn.1671-1815.2403210
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针对当前电网公司逾龄资产体系较大且逾龄设备管理相对薄弱的现状,提出一种考虑输配电价影响的逾龄资产退役优化决策方法。首先,根据输配电价改革的政策方案,建立省级电网在不同电压等级下的输配电价核算模型;其次,以全投资周期收益最高为优化目标、以逾龄资产退役时间和退役规模为决策变量,建立逾龄资产退役规划模型,并通过滚动优化和反馈矫正过程,确保在每个阶段逾龄资产退役规模能够跟踪期望值,以在满足系统可靠性的前提下尽可能使电网公司效益最大化;最后,以某省${110}\mathrm{\;{kV}}$电压等级电网为例验证了模型的有效性以及在提高投资效率方面的优越性。

输配电价改革  /  逾龄资产  /  滚动优化  /  退役规模  /  退役时间

Given the prevalent issue of aging assets within power grid companies and the subpar management of aging equipment, a decision-making approach was introduced for optimizing the decommissioning of aging assets, taking into account the influence of transmission and distribution tariffs. Firstly, in accordance with the policy framework for reforming transmission and distribution tariffs, an accounting model for transmission and distribution tariffs for provincial power grids operating at varying voltage levels was developed. Secondly, the decommissioning planning model for over-age assets was established with the optimization objective of achieving the highest return throughout the investment cycle. The decision variables of time and scale for decommissioning were utilized in this model. Through a process of rolling optimization and feedback correction, the model ensured that the scale of decommissioning for overage assets in each stage aligns with the desired value, thereby meeting the premise of system reliability. Finally, the efficacy of the model and its ability to enhance investment efficiency were demonstrated through the examination of the${110}\mathrm{{kV}}$voltage level grid in a specific province.

transmission and distribution price reform  /  aged assets  /  multi-stage rolling optimization  /  decommissioning scale  /  decommissioning time
禹红伟, 刘文霞, 王馥馨, 胡皖涛, 李瞳, 王晓晖. 计及输配电价影响的逾龄资产退役优化决策. 科学技术与工程, 2025 , 25 (8) : 3258 -3267 . DOI: 10.12404/j.issn.1671-1815.2403210
Hong-wei YU, Wen-xia LIU, Fu-xin WANG, Wan-tao HU, Tong LI, Xiao-hui WANG. Optimal Decommissioning Decisions for Aged Assets Taking into Account the Impact of Transmission and Distribution Tariffs[J]. Science Technology and Engineering, 2025 , 25 (8) : 3258 -3267 . DOI: 10.12404/j.issn.1671-1815.2403210
有效资产是核算输配电价的依据, 也是决定电网企业公司可持续发展的核心要素之一, 根据《中共中央国务院关于进一步深化电力体制改革的若干意见》(中发 [2015] 9 号)等文件规定,电网企业输配电准许总收入的核定原则是 “准许成本加合理固定资产(即逾龄资产)不能计算折旧费,在准许收益中,逾龄资产不纳入有效资产进行计算${}^{\left\lbrack 1\text{-}2\right\rbrack }$。因此, 虽然部分逾龄资产由于状态良好仍在服役, 延缓了设备升级改造, 但在成本监审过程中, 逾龄资产仅能获得准许成本中的运维费部分, 无法足额获得准许成本、准许收益。如果占比较大将直接影响电网企业准许总收入, 进而影响输配电价。当前, 电网逾龄资产占比过高,随着快速发展期电网建设高速增长,历年投产的固定资产陆续提足折旧,未来逾龄资产规模将持续“攀墙”并呈高速增长态势。在此背景下, 深入分析逾龄资产生的多维影响, 优化其退役策略,对提高电网企业运营效率,维护电网安全运行具有重要的意义。
为适应输配电价改革,逾龄资产如何进行合理有效的管理已成为当前研究热点。文献 [3] 研究发现, 目前电网企业逾龄资产大部分属于逾龄折旧并非技术逾龄特点, 与资产本身的技术寿命年限存在较大差异,存在部分资产被提前逾龄。文献 [4-7] 研究表明, 电网逾龄资产规模过大导致有效资产减少, 造成核价基数减少, 无法获得准许收入足额回报。文献[8]分析了逾龄资产安全系数低、经济效益差、运维成本高等特点, 提出应及时进行更新改造, 以实现安全有序退出, 扩大电网有效资产规模提升效益。文献[9] 研究表明,大量逾龄资产的存在, 降低了公司资产负债率, 虚增了电网利润, 增加了缴税额度, 不利于新型电力系统投资和企业发展。文献 [10] 研究发现, 继续使用逾龄资产, 能使企业的经营成本、事业单位的经费支出实现最小化, 使资产使用达到效用最大化, 虽然这对于社会资源的配置来说是经济的, 但是对逾龄资产继续使用带来安全风险考虑不足。文献 [11] 研究表明, 随着逾龄设备使用年限的增加, 设备缺陷率、负载率急剧攀升,运维检修、可靠性成本逐年增加,通过引入全寿命周期成本模型, 提出了考虑设备稳定性和可靠性的联合退役策略。文献[12-13] 通过对设备服役状态下可靠性分析及剩余寿命预测, 从而确定设备最佳退役年限。文献 [14-15] 提出一种考虑逾龄资产差异化技改投资的方法, 在技改总投资金额、技改次数和技改项目期限已知的条件下, 以技改后的资产整体使用年限最长为目标函数, 以评估年之前逾龄资产年末资产净值大于等于资产残值为主要约束条件, 建立了逾龄资产逐年退役的优化规划模型。但只考虑了资产本身,没有考虑资产变化对系统安全风险和总体经济性的影响。文献[16]依据 “资产墙” 提前预测未来技改投资需求及资产更新改造的压力, 促使资产管理策略从定性决策向定量决策转化。文献 [17] 通过建立逾龄资产清单以及对逾龄资产的残值进行评估来完善逾龄资产价值管理模式。文献 [18] 认为, 根据输配电价监审管理办法, 逾龄资产不被纳入有效资产中, 从而影响输配电价的核定, 对电网收益产生影响。综上可知, 前人对逾龄资产正反两方面效益进行了分析,定性说明了针对逾龄资产管理改进的措施, 但没有量化继续使用或者退役对系统、企业收益、 安全性等方面的影响, 无法对高比例逾龄资产的退役策略给出具体指导。
为此, 提出一种计及输配电价影响的逾龄资产退役优化决策方法。通过分析逾龄资产退役对准许成本、准许收益和税金的影响,建立考虑逾龄资产退役的输配电价核算模型。以逾龄资产每阶段退役比例为控制变量, 以全投资周期收益最高为目标函数, 考虑逾龄资产对系统经济性和安全性的影响, 以电网风险水平、输配电价和运行维护费率为约束, 在此基础上, 考虑逾龄资产逐年变化情况, 建立逾龄资产退役决策多阶段滚动优化模型[19-21]。通过模型求解及算例分析表明逾龄资产安全有序的退出运行, 不仅能够提升电网可靠性, 而且为输配电价改革背景下电网公司逾龄资产退役决策和政府部门相关政策的制定等提供参考依据。
根据《省级电网输配电价定价办法》要求, 省级电网输配电价在每一监管周期开始前核定,监管周期为 3 年, 依据不同电压等级和用户的用电特性和成本结构核定电网输配电价。以${110}\mathrm{{kV}}$ 电压等级大工业用户为例, 建立考虑逾龄资产退役的输配电价核算模型。
根据定价办法中的要求, 输配电准许收入由准许成本、准许收益和税金构成。各电压等级电力用户第$t$ 年的准许收入$I\left(t\right)$ 可表示为
$ I\left(t\right)= C\left(t\right)+ R\left(t\right)+ L\left(t\right)$
式 (1) 中:$C\left(t\right)$ 为第$t$ 年输配电网的准许成本;$R\left(t\right)$ 为第$t$ 年输配电网的准许收益;$L\left(t\right)$ 为第$t$ 年输配电网的价内税金。
电网企业准许收入核算方式如图1 所示。
在输配电价核算中, 准许成本是电网公司在运营过程中各项成本的支出, 这些成本被纳入输配电价核算中使电网企业能够覆盖其运营成本并获得合理回报, 确保电力市场的稳定运行和供需平衡, 从时间维度上准许成本区分基期准许成本和监管周期内预计新增或减少的准许成本分别核定, 可表示为
$ C\left(t\right)= C\left({t}_{0}\right)+ {\Delta C}\left(t\right)$
式 (2) 中:${t}_{0}$ 为基准年;${\Delta C}\left(t\right)$ 为第$t$ 年计及逾龄资产退役及新增后的电网准许成本变化量。
考虑逾龄资产不再计提折旧,但是逾龄资产退役后新购输配电相关资产的成本可以回收, 因此, 第$t$ 年计及逾龄资产退役及新增后的电网准许成本变化量${\Delta C}\left(t\right)$ 可表示为
${\Delta C}\left(t\right)= \left\lbrack {\mathop{\sum }\limits_{{n \in N}}{V}_{\mathrm{{cfa}}, n}\left(t\right)- \mathop{\sum }\limits_{{m = 1}}^{M}{V}_{\mathrm{{jfa}}, m}\left(t\right)}\right\rbrack {r}_{\mathrm{{de}}}$
式 (3) 中:${V}_{\mathrm{{cfa}}, n}\left(t\right)$ 为第$t$ 年逾龄设备退役后,为依旧保证系统供电能力而更换的新设备投资成本;${V}_{\mathrm{{jfa}}, m}\left(t\right)$ 为第$t$ 年电网新增逾龄资产原值;$N$ 为待退役逾龄设备集;$M$ 为新增逾龄设备集;${r}_{\mathrm{{de}}}$ 为定价折旧率。
准许收益是指电网公司在电价核算中允许在收回成本的基础上获取合理回报, 确保电力企业能够覆盖成本并获取利润, 同时又不会过度滥用其市场地位导致不公平的价格对电力用户造成伤害。准许收益根据电网有效资产和准许收益率共同核定, 电网可计提收益的有效资产包含基期可计提收益的有效资产和监管周期内预计新增或减少的有效资产,可表示为
$ A\left(t\right)= A\left({t}_{0}\right)+ {\Delta A}\left(t\right)$
式 (4) 中:$A\left(t\right)$ 为第$t$ 年电网可计提收益的有效资产;$A\left({t}_{0}\right)$ 为电网基期资产净值。
监管周期内预计新增可计提收益的有效资产根据预计新增输配电固定资产原值扣减监管周期相应折旧费核定,电网有效资产变化量${\Delta A}\left(t\right)$ 可表示为
${\Delta A}\left(t\right)= \mathop{\sum }\limits_{{n \in N}}{V}_{\mathrm{{cfa}}, n}\left(t\right)\left({1 -{r}_{\mathrm{{de}}}}\right)- \mathop{\sum }\limits_{{m = 1}}^{M}{V}_{\mathrm{{jfa}}, m}\left(t\right){r}_{\mathrm{{de}}}$
电网公司第$t$ 年准许收益$R\left(t\right)$ 可表示为
$ R\left(t\right)= A\left(t\right) r $
式 (6) 中:$r$ 为准许收益率。
准许收益率由电网固定资产收益率和债务利率共同决定, 可表示为
$ r ={r}_{\mathrm{e}}\left({1 - l}\right)+ {r}_{\mathrm{d}}l $
式(7)中:${r}_{\mathrm{e}}$ 为权益资本收益率;${r}_{\mathrm{d}}$ 为债务资本收益率;$l$ 为电网资产负债率。
价内税金是指除增值税外的其他税金,包括所得税、城市维护建设税、教育费附加, 依据现行国家相关税法规定核定, 考虑城市维护建设税和教育费附加较小,不再考虑。所得税以电网有效资产为基础进行核定, 输配电网的所得税为
$ L\left(t\right)= \frac{A\left(t\right){r}_{\mathrm{e}}\left({1 - l}\right)}{1 -{r}_{\text{suode }}}{r}_{\text{suode }}$
式 (8) 中:${r}_{\text{suode }}$ 为电网所得税率。
逾龄资产退役影响准许成本及有效资产核算, 继而影响输配电价计算。考虑逾龄资产退役的省级电网不同电压等级的平均输配电价由该监管周期输配电价预计回收的准许收入和本电压等级传输的输配电量共同决定, 可表示为
$ P =\frac{I}{Q}= \left\{{C\left({t}_{0}\right)+ \mathop{\sum }\limits_{{t = 1}}^{T}{\Delta C}\left(t\right)+ }\right.\\\left.{\left\lbrack {A\left({t}_{0}\right)+ \mathop{\sum }\limits_{{t = 1}}^{T}{\Delta A}\left(t\right)}\right\rbrack \left\lbrack {r +\frac{{r}_{\mathrm{e}}\left({1 -{r}_{\mathrm{{al}}}}\right){r}_{\text{suode }}}{1 -{r}_{\text{suode }}}}\right\rbrack }\right\}{Q}^{-1}$
式 (9) 中:$P$ 为考虑逾龄资产退役的输配电价;$I$ 为通过输配电价回收的准许收入;$T$ 为监管周期长度,$T = 3;Q$ 为电网规划周期内平均输配电量。
考虑电网企业新增逾龄资产不确定性问题及输配电价每 3 年核算一次,当前阶段逾龄资产退役优化结果不仅对本阶段输配电价核算产生影响, 而且对未来阶段核价基数均会造成影响, 该决策涉及多个阶段和多个变量的复杂优化问题, 通过建立多阶段滚动优化模型, 解决电网公司在逾龄资产退役优化中的策略制定过程。多阶段滚动优化模型用于对长期规划和短期优化决策, 在逾龄资产退役决策中平衡成本、风险和电价影响, 实现最优的决策结果, 通过考虑逾龄资产的技术状况、成本效益、电价影响等因素,帮助电力公司制定合理的退役策略,实现电网企业效益最大化和风险最小化。
按照多阶段优化的原理和思想[22-24],将输配电价改革下逾龄资产退役优化阶段进行划分, 示意图如图2 所示。
输配电价改革背景下逾龄资产多阶段滚动优化决策思路为:以 3 年为一个阶段, 每阶段初年进行滚动优化计算,得出每一年退役规模,在已知每年逾龄资产规模基础上, 将前 3 年作为第一阶段结果执行, 下一阶段进行后续年限的计算, 形成滚动优化过程。首先,根据当前电网逾龄资产相关参数、 资产规模、输配电价核算参数等信息优化决策初期阶段 1 的逾龄资产退役规模;其次,综合考虑退役及新增逾龄资产基础上优化决策阶段 2 的逾龄资产退役规模,以满足电网供电可靠性要求;以此类推,直至阶段$K$ 时,计及$K - 1$ 阶段优化后的逾龄资产及该阶段新增逾龄资产优化第$K$ 阶段退役规模,使所有阶段系统供电可靠性及用电需求得到满足。
根据多阶段滚动优化理论,针对逾龄资产退役优化决策问题分别建立不确定预测模型和优化模型。其中,控制变量为每个阶段内逾龄资产退役规模, 输入变量为当前电网逾龄资产规模及输配电价核算相关参数, 输出变量为电网逾龄资产最佳退役计划,预测模型为根据 “资产墙” 预测规划周期内新增逾龄资产规模及考虑逾龄资产退役后系统期望缺供电量[25],决策变量为逾龄资产退役时间及退役规模, 以全规划周期内最终收益最大为目标, 在满足电网安全风险水平、输配电价和运行维护费率等约束的条件下,求解当前阶段逾龄资产退役规模及该阶段每个日历年退役规模。具体框架如图3 所示。
上述策略的具体步骤如下。
步骤 1 首先确定固定规划周期内第 1 个阶段的退役方案。在第 1 个阶段以$K\left({\text{取 }5}\right)$ 作为固定规划周期进行整体寻优, 即根据第 1 个阶段的逾龄资产规模和第 1 个阶段的新增逾龄资产预测数据, 采用 3.3.1 节的目标函数和 3.4 节的模型求解方法获得全局最优的逾龄资产退役方案, 但在该时间窗口内仅优化第 1 个阶段逾龄资产退役计划, 并记录各阶段在第 1 阶段退役方案执行前后逾龄资产规模的变化情况, 为下一阶段逾龄资产退役决策提供数据支撑。
步骤 2 根据时序不断向前推移连续确定各阶段在第$2 - K$ 个阶段的逾龄资产退役决策方案。第 1 个阶段优化决策结束后, 决策优化第 2 个阶段逾龄资产退役计划,此时逾龄资产实时数据更新为第 2 个阶段的逾龄资产规模和第 2 个阶段新增逾龄资产预测值,此时以$K - 1$ 个阶段为规划周期,基于上一阶段优化决策后的各窗口的状态按照步骤 1 重新优化全局最优的逾龄资产退役方案, 但在该时间断面仅执行第 2 个阶段的退役计划, 并记录各阶段在第 2 阶段退役方案执行前后逾龄资产规模的变化情况,为后续阶段逾龄资产退役优化提供数据支撑。待第 2 个阶段优化结束后再次更新电网逾龄资产规模及新增逾龄资产预测数据, 滚动连续对第 3 个阶段逾龄资产退役规模进行优化。之后按照相同的步骤对后续阶段逾龄资产的退役规模持续优化,直至完成第$K$ 个阶段逾龄资产退役方案的确定。
以电网收益最大为优化目标, 考虑逾龄资产退役引起输配电价变化后的动态收益及逾龄资产规模变动后的成本变化,电网最终收益$f$ 为售电收益${f}_{1}$ 和总成本${f}_{2}$ 的差值。
$\max f ={f}_{1}- {f}_{2}$
按照输配电价改革后的电价核算方法, 在该核算方法下电网逾龄资产经济性退役优化决策总收人为
${f}_{1}= P\left({1 -{R}_{\text{loss }}}\right) Q $
式(11)中:${R}_{\text{loss }}$ 为网损率。
输配电价改革背景下逾龄资产退役成本主要由电网建设成本${C}_{\text{con }}$、运行成本${C}_{\text{ope }}$、退役处置成本${C}_{\mathrm{{ocp}}}$ 及可靠性成本${C}_{\mathrm{{rel}}}$ 构成,即
${f}_{2}= {C}_{\text{con }}+ {C}_{\text{ope }}+ {C}_{\text{ocp }}+ {C}_{\text{rel }}$
(1)电网初始投资成本。电网初始投资成本为逾龄资产退役依旧保证系统供电能力而更换的新设备投资成本, 具体可表示为
${C}_{\text{con }}= \mathop{\sum }\limits_{{n \in N}}{V}_{\text{cfa }, n}$
(2)电网运行成本。电网运行成本为考虑逾龄资产退役新设备的运行维护费及电网企业的运营费用,具体可表示为
${C}_{\text{ope }}= {C}_{\mathrm{e}}+ {C}_{\mathrm{r}}+ {C}_{\mathrm{p}}+ {C}_{\mathrm{o}}\\= \mathop{\sum }\limits_{{n \in N}}{V}_{\text{cfa }, n}\left({\alpha +\beta +\gamma +\omega }\right)$
式(14)中:${C}_{\mathrm{c}}\text{、}{C}_{\mathrm{r}}\text{、}{C}_{\mathrm{p}}$${C}_{\mathrm{o}}$ 分别为电网新增的材料费、修理费、职工薪酬和其他费用;$\alpha \text{、}\beta \text{、}\gamma$$\omega$ 分别为电网材料费率、修理费率、人工费率和其他运营费率。
(3)退役处置成本。逾龄设备退役处置费用包括设备退役处置所需的费用, 具体可表示为
${C}_{\text{ocp }}= \mathop{\sum }\limits_{{n \in N}}{V}_{\text{cfa }, n}\left\lbrack {\eta \left({1 +\delta }\right)- \varphi)}\right\rbrack $
式 (15) 中:$\eta$$\delta$ 分别为设备安装费占设备购置费比例、设备报废成本占安装调试费比例,分别取${0.062}\text{、}{0.32};\varphi$ 为设备残值率,一般取$5\%$
(4)电网故障成本。电网故障成本选取期望缺供电量作为故障损失费,即可靠性成本,具体可表示为
${C}_{\text{rel }}= Q{\lambda }_{\text{ave }}{k}_{\mathrm{d}}$
式(16)中:${\lambda }_{\text{ave }}$ 为系统平均故障率;${k}_{\mathrm{d}}$ 为缺电损失评价系数,元/($\mathrm{{kW}}\cdot \mathrm{h}$)。
新设备处于早期失效期时间为 1 年, 超过折旧年限成为逾龄资产进入损耗失效期,通过聚类将逾龄资产分为 3 类, 平均故障率计算公式为
${\lambda }_{\text{ave }}= {R}_{1}{\lambda }_{1}+ {R}_{2}{\lambda }_{2}+ {R}_{3}{\lambda }_{3}$
式(17)中:${R}_{1}$${R}_{2}$${R}_{3}$ 分别为电网资产原值在 “浴盆曲线” 3 个阶段所占比例;${\lambda }_{1}\text{、}{\lambda }_{2}\text{、}{\lambda }_{3}$ 分别为设备在 “浴盆曲线”3 个阶段平均故障率。
变压器可靠性参数参考文献 [26] 中故障率曲线的威布尔分布函数确定,如表1 所示。
约束条件包含系统风险水平约束、电网输配电价约束、逾龄资产技改规模约束及运行维护费率约束,具体表达式为
(1)系统风险水平约束。系统期望缺供电量满足用户可接受期望缺供电量, 即
${\mathrm{{EENS}}}_{\mathrm{t}}< {\mathrm{{EENS}}}_{\text{ref }}$
式(18)中:${\mathrm{{ERNS}}}_{\mathrm{t}}$ 为年系统期望缺供电量;${\mathrm{{ERNS}}}_{\text{ref }}$ 为用户可接受期望缺供电量。
(2)电网输配电价约束。输配电价在逐步调整过程中将趋于稳定, 参与电力市场化交易用户的输配电价水平按照不高于政府定价执行, 即
${P}_{i}\leq {P}_{\text{ref }}$
式 (19) 中:${P}_{i}$ 为第$i$ 个输配电价测算周期的输配电价,每 3 年为一个测算周期;${P}_{\text{ref }}$ 为政府最高核定输配电价,为 0.1710 元$/\mathrm{{kW}}\cdot \mathrm{h}$
(3)运行维护费率约束。
$\alpha +\beta +\gamma +\omega \leq {4.5}\%$
式 (20) 中,电网材料费率$\alpha$、修理费率$\beta$、人工费率$\gamma$ 和其他运营费率$\omega$ 合计按不高于监管周期新增输配电固定资产原值的 4.5% 核定。
构建滚动优化线性模型,在 MATLAB 2017a 中建模并进行求解, 求解流程如图4 所示, 具体步骤如下。
步骤 1 输入基础参数,初始化决策变量${V}_{\mathrm{{cfa}}}$
步骤 2 设置初始决策阶段$i = 1$
步骤 3 根据电网“资产墙”预测当前阶段新增逾龄资产规模。
步骤 4 基于当前阶段逾龄资产及新增逾龄资产规模优化退役规模${V}_{\mathrm{{cfa}}}$,并通过式 (1)$\sim$ 式 (8) 计算准许收入。
步骤 5 输入当前阶段省级电网平均输配电量, 按照式 (10) 计算得到考虑逾龄资产退役后的输配电价。
步骤 6 按照步骤 4 得到的输配电价由式 (11) 计算得到电网逾龄资产经济性退役优化决策售电收入。
步骤 7 根据式 (12)~ 式 (17) 计算输配电价改革背景下逾龄资产退役投资成本。
步骤 8 在步骤 5 、步骤 6 基础上计算当前阶段最终收益。
步骤 9 判断该阶段电网收益是否最大,若$f \neq$ $\max f$,转至步骤 3,否则$i = i + 1$
步骤 10 根据逾龄资产预测值及退役规模更新逾龄资产规模。
步骤 11 判断规划周期是否结束。若$i \leq K$, 转至步骤 3,否则输出最优${V}_{\mathrm{{cfa}}}$ 决策结果。
以某省级电网为例, 对该省逾龄资产退役规模进行优化, 该省数据如表2表3图5 所示。
求解输配电价改革下逾龄资产退役规模, 将规划周期划分为 5 个阶段, 每个阶段代表1 个监管周期,各监管周期持续时间均为 3 个日历年,逾龄资产退役优化结果如图5 所示。
图5 可以看出, 随着逾龄资产逐步退出现役新资产的投运,电网中可计提收益的有效资产及用来折旧的固定资产规模提升,核价基数增加,相较于基期输配电价总体呈上涨趋势,由基期 0.1701 元/$\left({\mathrm{{kW}}\cdot \mathrm{h}}\right)$ 涨至0.1707 元/$\left({\mathrm{{kW}}\cdot \mathrm{h}}\right)$,涨幅 0.000 6 元/$\left({\mathrm{{kW}}\cdot \mathrm{h}}\right)$。输配电价由基期准许收入和监管周期内新增/减少准许收入共同核定,而监管周期内新增/减少的准许收入与逾龄资产新增规模及退役速率相关, 电网新增逾龄资产规模由“资产墙”预测得到, 当电网逾龄资产退役规模大于新增逾龄资产规模时,新增准许成本高于减少的部分, 电网可计提收益的有效资产规模增大, 输配电价提升效果明显; 反之, 若逾龄资产退役规模小于新增规模,准许成本减少,输配电价呈下降趋势。由以上分析可知, 逾龄资产退役规模和新增逾龄资产规模的差值共同影响输配电价的核定,为保证电网输配电价的合理性和稳定性, 两者差值越小越有利于电网企业发展。售电收益作为电网主要收入来源, 在售电量保持不变情况下随输配电价提升电网侧售电收入增加, 但考虑逾龄资产退役后的成本因素, 主要由初始投资成本和可靠性成本决定, 若退役速度过快, 为保证系统供电能力而更换的新设备投资将变大, 初始投资成本变高, 分摊到每年的折旧费用随之提升。但随着电网逾龄资产逐步退出现役,系统故障率显著降低, 供电可靠性提升, 由期望缺供电量造成的故障损失费用大幅减少。综上, 考虑电网以输配电价增长为系统驱动因素盈利的模式, 逾龄资产退役策略的实施有助于稳定输配电价, 降低维护成本和运营成本, 提高了电力公司的整体效益, 使资产管理更加经济高效。各监管周期成本及收益如图6表4 所示。
表4 可知, 售电收益作为电网主要收入来源, 在售电量保持不变情况下和输配电价成正比关系。成本方面, 主要由初始投资成本和可靠性成本决定,两者与电网逾龄资产规模及逾龄资产退役速率相关。若逾龄资产退役速度加快, 为保证系统供电能力而更换的新设备投资变大,初始投资成本变高, 但随着电网逾龄资产规模的减少, 系统故障率降低, 供电可靠性水平显著提升, 由期望缺供电量造成的故障损失费用大幅减少,随着逾龄资产安全有序退役现役, 电网成本逐步降低, 使电网最终收益有所提升。
考虑未来一段时间内逾龄资产规模将持续“攀墙”并呈高速增长态势, 且各省地市公司逾龄资产规模存在差异性。因此, 引入逾龄资产新增规模倍数${k}_{\mathrm{d}}$ 来量化各省市公司逾龄资产规模的差异性,根据逾龄资产规模和技术状况差异, 制定相应的退役计划和措施, 有效提高电网公司的整体效益和资产利用率。针对新增逾龄资产规模分别取增长倍数${k}_{\mathrm{d}}= {0.5}\text{、}{k}_{\mathrm{d}}= 1$ 进行仿真计算,考虑新增逾龄资产规模差异化退役优化结果如图7 所示。
图7 可知, 逾龄资产退役规模和电网逾龄资产规模总体成正比关系, 逾龄资产退役规模随着电网新增逾龄资产规模增长而增长, 使电网逾龄资产规模总体保持在可控范围内,在满足供电可靠性及效益最大化目标前提下安全平稳退出运行。但在电网可持续发展要求及省级电网输配电价约束条件下, 随着电网新增逾龄资产规模持续扩大, 逾龄资产退役规模难以全覆盖新增逾龄资产规模,两者规模差越来越大, 使电网逾龄资产总规模增大, 系统可靠性成本骤增,为满足系统风险水平约束,需采取相应措施使逾龄资产大规模退出现役,但这也意味着更多的投资成本, 大规模退役难以满足电网可持续发展要求。因此, 需通过对每个监管周期的每个日历年持续优化退役决策, 小规模多次退出现役, 缩小逾龄资产和新增逾龄资产规模差值, 保证逾龄资产安全平稳退出运行, 使电网逾龄资产总体规模保持较低水平。
为说明所提方法在输配电价改革后的有效性与输配电价改革对逾龄资产退役决策的影响, 在上述算例基础上,采用输配电价改革前电网以购销差价方式获取收益建立逾龄资产退役优化模型, 该省输配电价改革前[购入电价 0.3410 元$/\left({\mathrm{{kW}}\cdot \mathrm{h}}\right)$,售出电价 0.5122 元/(kW·h)] 购销差价 0.1712 元/(kW·h)。方案 1 为考虑输配电价改革后的逾龄资产退役优化方案, 方案 2 为输配电价改革前的逾龄资产退役优化方案,优化结果如图8 所示。
当前退役策略下, 电网单位电量营销收入由购销差价决定, 在售电量保持不变情况下售电收益为定值, 因此决策逾龄资产退役规模时考虑成本最小即可。由图8 可知, 相较于方案 1 方案 2 的逾龄资产退役规模具有间歇性特点, 由于方案 2 更多关注成本变化且不用考虑电网输配电价约束, 因此没有逾龄资产退役规模约束。电网成本主要由可靠性成本和购置成本决定, 当前阶段逾龄资产退役规模越大, 处于 “浴盆曲线” 早期失效期的资产规模占比越大, 由于该阶段设备故障率较高, 故系统可靠性成本高, 但下一阶段处于早期失效期的资产过渡至随机失效期,该阶段资产规模占比增加,系统平均故障率降低, 由期望缺供电量造成的故障损失费用大幅减少,可靠性提升效果明显,后续阶段可采取不退或者少退策略使成本最小化。该方案下, 当系统可靠性不满足要求时, 采用大规模退役方式以大幅提升系统可靠性效益, 减少初始购置成本和可靠性效益的差值, 保障电网安全供电水平的同时使电网成本最小化,具体成本及收益如表5 所示。
表5 可以看出, 方案 2 采用购销差价 0.1712 元/$\left({\mathrm{{kW}}\cdot \mathrm{h}}\right)$ 高于改革后各监管周期的输配电价, 因此在负荷相同的情况下, 此时方案 2 售电收入高于改革后售电收入。成本方面, 方案 2 较方案 1 逾龄资产退役规模较小, 电网剩余逾龄资产规模远高于方案 1 , 产生更多的可靠性成本, 此时最终收益有所减少。
对比可知, 输配电价改革后的方案更具科学性和灵活性, 能够更好地根据实际情况做出决策, 降低决策风险。输配电价改革对电网收益成本产生影响, 从而影响逾龄资产退役规模。由于输配电价改革后各监管周期的核定电价低于改革前电价, 改革后售电收入有所减少,但随着逾龄资产退役新设备投运,可靠性成本大幅降低,最终收益有了较大提升。
随着电网建设的不断发展, 电网资产规模持续扩大, 由于资产财务折旧年限普遍低于定价折旧年限, 逾龄资产体系越来越庞大, 双重压力给电网公司资产管理带来新的挑战, 传统模式下的退役决策无法有效应对电价改革后的需求。为此, 提出一种输配电价改革背景下电网逾龄资产退役优化决策方法。通过算例将该模型分别与考虑逾龄资产不同规模及输配电价改革前退役方法对比, 验证本文方法的有效性和相对优势, 得出如下结论。
(1)本文模型采用输配电价改革后电价核算方式,随着逾龄资产逐步退出现役, 电网可计提收益的有效资产及用来折旧的固定资产规模提升,核价基数增加, 售电收益提升, 而可靠性成本大幅降低, 优化结果可为电网公司逾龄资产退役决策和政府部门相关政策的制定等提供参考依据。
(2)考虑各省地市公司新增逾龄资产规模存在差异性, 通过分析在不同占比情况下逾龄资产退役策略, 为后续不同地市公司根据自身实际情况采取相应的策略。
(3)通过建立的模型,以输配电价增长为系统驱动因素,考虑输配电价改革背景下逾龄资产退役策略可提高电网投资决策的经济性, 各监管周期成本相较于改革前有大幅度降低。
(4)电网资产规模大、种类繁多、分布广泛,所提出的退役策略方法较为宏观且针对颗粒度较大的逾龄资产,在应对逾龄资产差异化退役问题时, 依据当前逾龄资产技改规模考虑设备逾龄时间、健康状况等因素进行单体设备精准抉择有待进一步研究。
  • 国家电网公司总部科技项目(5100-202456030A-1-1-ZN)
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2025年第25卷第8期
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doi: 10.12404/j.issn.1671-1815.2403210
  • 接收时间:2024-04-30
  • 首发时间:2025-07-29
  • 出版时间:2025-03-18
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  • 收稿日期:2024-04-30
  • 修回日期:2024-12-26
基金
国家电网公司总部科技项目(5100-202456030A-1-1-ZN)
作者信息
    1 新能源电力系统国家重点实验室 北京 102206
    2 国网经济技术研究院有限公司 北京 102200

通讯作者:

*刘文霞(1967-),女,汉族,北京人,博士,教授。研究方向:电力系统规划与可靠性、电力系统风险评估。E-mail: liuwenxia001@163.com。
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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