Load Profile Analysis for Mitigating Load-Shedding in Central Africa: Case of Kinshasa  

作　　者：Ngondo Otshwe Josue Bin Li Nawaraj Kumar Mahato Ngouokoua Jaime Ngondo Otshwe Josue;Bin Li;Nawaraj Kumar Mahato;Ngouokoua Jaime(School of Electrical and Electronics Engineering, North China Electric Power University, Beijing, China;Department of Electrical Engineering, Mapon University, Kindu, RD Congo;Research Center for Energy Electric Power Information Security, North China Electric Power Information Security, North China Electric Power University, Beijing, China)

机构地区：[1]School of Electrical and Electronics Engineering, North China Electric Power University, Beijing, China [2]Department of Electrical Engineering, Mapon University, Kindu, RD Congo [3]Research Center for Energy Electric Power Information Security, North China Electric Power Information Security, North China Electric Power University, Beijing, China

出　　处：《Journal of Power and Energy Engineering》2024年第8期1-19,共19页电力能源（英文）

摘　　要：Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.

关 键 词：Statistical Analysis Load Profile Load Shedding Kinshasa Distribution Network Distribution Reliability Indices 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]