In the context of maintaining energy security and implementing low-carbon development, ensuring the power system reliability is becoming increasingly challenging. The interdependence between power industry and other sectors within the supply chain network exposes the entire economy to unpredictable higher-order economic impact resulting from power interruption. To explore the heterogeneous regional effects by improving power supply reliability in mitigating national economic losses, this study employs an agent-based complex network supply chain model to conduct an economic assessment of power supply reliability in China. Using a top-down approach, the study estimates the direct economic losses of production activities due to power interruption in China in 2018 and incorporates them as external shocks in the complex network model to simulate the higherorder indirect economic losses caused by power disruption in the supply chain network on a daily basis. By setting up 298 scenarios that reduce power outage duration in each region one by one, the study identifies 15 key regions for safeguarding power supply reliability. Enhancing the power supply reliability in these areas can result in an average reduction of indirect economic losses ranging from CNY 439 million to CNY 1.96 billion nationwide, representing a decrease of 0.39% to 1.76% compared to the baseline scenario. The findings of this research may provide guidance for relevant departments in identifying priority areas, assessing the value of power supply reliability, considering additional costs for power security maintenance, and formulating policy implications for the development of power security construction in different regions.
[1] 汤广福,周静,庞辉,等.能源安全格局下新型电力系统发展战略框架[J].中国工程科学, 2023, 25(2):79-88.
[2] 饶宏,韩丰,陈政,等.我国电力安全供应保障策略研究[J].中国工程科学, 2023, 25(2):100-110.
[3] Ovaere M, Heylen E, Proost S, et al. How detailed value of lost load data impact power system reliability decisions[J]. Energy Policy, 2019, 132:1064-1075.
[4] 许丹,刘恺,丁强,等.电力市场中备用容量需求评估研究——基于均衡分析制定备用机组的竞价策略[J].价格理论与实践, 2022(7):175-179.
[5] 朱继忠,喻芸,谢平平,等.美国稀缺定价机制及对我国现货市场建设的启示[J].南方电网技术, 2019, 13(6):37-43, 75.
[6] 黄姗姗,叶泽,罗迈,等.中国电力中长期市场分时段交易价格形成机制及模型[J].中国电力, 2023, 56(1):17-27.
[7] Lavin L, Murphy S, Sergi B, et al. Dynamic operating reserve procurement improves scarcity pricing in PJM[J]. Energy Policy, 2020, 147(12):111857.
[8] 陈启鑫,吕睿可,郭鸿业,等.面向需求响应的电力用户行为建模:研究现状与应用[J].电力自动化设备, 2023, 43(10):23-37.
[9] Gorman W. The quest to quantify the value of lost load:A critical review of the economics of power outages[J]. The Electricity Journal, 2022, 35(8):107187.
[10] 中华人民共和国国家发展和改革委员会令.《电力可靠性管理办法(暂行)》[EB/OL].(2022-04-16)[2023-11-18]. www.gov.cn/zhengce/zhengceku/2022-04/25/content_5687101.htm.
[11] de Nooij M, Koopmans C, Bijvoet C. The value of supply security:The costs of power interruptions:Economic input for damage reduction and investment in networks[J]. Energy Economics, 2007, 29(2):277-295.
[12] Broberg T, Persson L. Is our everyday comfort for sale?Preferences for demand management on the electricity market[J]. Energy Economics, 2016, 54(2):24-32.
[13] Leahy E, Tol R S J. An estimate of the value of lost load for Ireland[J]. Energy Policy, 2011, 39(3):1514-1520.
[14] Wing I S, Rose A Z. Economic consequence analysis of electric power infrastructure disruptions:General equilibrium approaches[J]. Energy Economics, 2020, 89(3):104756.
[15] Baik S, Hanus N L, Sanstad A H, et al. A hybrid approach to estimating the economic value of enhanced power system resilience[R]. Berkeley:Lawrence Berkeley National Laboratory (LBNL), 2021.
[16] 何永秀,黄文杰,谭忠富,等.基于投入-产出法的电力失负荷价值研究[J].电网技术, 2006, 30(1):44-49.
[17] 谭显东,胡兆光.基于投入产出法的电力失负荷价值研究拓展[J].电网技术, 2008, 32(1):51-55.
[18] He P J, Ng T S, Su B. Energy-economic recovery resilience with Input-Output linear programming models[J]. Energy Economics, 2017, 68:177-191.
[19] Chen H, Yan H B, Gong K, et al. Assessing the business interruption costs from power outages in China[J]. Energy Economics, 2022, 105:105757.
[20] Poudineh R, Jamasb T. Electricity supply interruptions:Sectoral interdependencies and the cost of energy not served for the Scottish economy[J]. The Energy Journal, 2017, 38(1):51-76.
[21] Akpeji K O, Olasoji A O, Gaunt C T, et al. Economic impact of electricity supply interruptions in South Africa[J]. SAIEE Africa Research Journal, 2020, 111(2):73-87.
[22] Henriet F, Hallegatte S, Tabourier L. Firm-network characteristics and economic robustness to natural disasters[J]. Journal of Economic Dynamics and Control, 2012, 36(1):150-167.
[23] Shughrue C, Werner B T, Seto K C. Global spread of local cyclone damages through urban trade networks[J]. Nature Sustainability, 2020, 3(8):606-613.
[24] Wenz L, Levermann A. Enhanced economic connectivity to foster heat stress-related losses[J]. Science Advances, 2016, 2(6):e1501026.
[25] 曲申,林瑾,王永豪,等.电力部门省际虚拟水流动模式与影响分析[J].北京理工大学学报(社会科学版), 2023, 25(2):45-56.
[26] Otto C, Willner S N, Wenz L, et al. Modeling loss-propagation in the global supply network:The dynamic agent-based model acclimate[J]. Journal of Economic Dynamics and Control, 2017, 83:232-269.
[27] Hallegatte S, Ranger N, Mestre O, et al. Assessing climate change impacts, sea level rise and storm surge risk in port cities:A case study on Copenhagen[J]. Climatic Change, 2011, 104(1):113-137.
[28] 曲申,陈炜明,刘丽静,等.后疫情重建阶段的碳排放趋势与减排策略研究[J].中国环境管理, 2021, 13(3):8-18.
[29] Willner S N, Otto C, Levermann A, et al. Global economic response to river floods[J]. Nature Climate Change, 2018, 8(7):594-598.