MULTIOBJECTIVE HEURISTIC SEARCH FOR SERVICE RESTORATION IN ELECTRIC DISTRIBUTION NETWORKS

2005 ◽  
Vol 38 (1) ◽  
pp. 145-150
Author(s):  
Vinícius Jacques Garcia ◽  
Paulo Morelato França
Author(s):  
David Wanik ◽  
Emmanouil Anagnostou ◽  
Brian Hartman ◽  
Thomas Layton

Abstract Electric distribution utilities have an obligation to inform the public and government regulators about when they expect to complete service restoration after a major storm. In this study, we explore methods for calculating the estimated time of restoration (ETR) from weather impacts, defined as the time it will take for 99.5% of customers to be restored. Actual data from Storm Irene (2011), the October Nor’easter (2011) and Hurricane Sandy (2012) within the Eversource Energy-Connecticut service territory were used to calibrate and test the methods; data used included predicted outages, the peak number of customers affected, a ratio of how many outages a restoration crew can repair per day, and the count of crews working per day. Data known before a storm strikes (such as predicted outages and available crews) can be used to calculate ETR and support pre-storm allocation of crews and resources, while data available immediately after the storm passes (such as customers affected) can be used as motivation for securing or releasing crews to complete the restoration in a timely manner. Used together, the methods presented in this paper will help utilities provide a reasonable, data-driven ETR without relying solely on qualitative past experiences or instinct.


2021 ◽  
Vol 11 (9) ◽  
pp. 4169
Author(s):  
Hirotaka Takano ◽  
Junichi Murata ◽  
Kazuki Morishita ◽  
Hiroshi Asano

The recent growth in the penetration of photovoltaic generation systems (PVs) has brought new difficulties in the operating and planning of electric power distribution networks. This is because operators of the distribution networks normally cannot monitor or control the output of the PVs, which introduces additional uncertainty into the available information that operations must rely on. This paper focuses on the service restoration of the distribution networks, and the authors propose a problem framework and its solution method that finds the optimal restoration configuration under extensive PV installation. The service restoration problems have been formulated as combinatorial optimization problems. They do, however, require accurate information on load sections, which is impractical in distribution networks with extensively installed PVs. A combined framework of robust optimization and two-stage stochastic programming adopted in the proposed problem formulation enables us to deal with the PV-originated uncertainty using readily available information only. In addition, this problem framework can be treated by a traditional solution method with slight extensions. The validity of the authors’ proposal is verified through numerical simulations on a real-scale distribution network model and includes a discussion of their results.


2001 ◽  
Vol 59 (3) ◽  
pp. 185-195 ◽  
Author(s):  
Antonino Augugliaro ◽  
Luigi Dusonchet ◽  
Eleonora Riva Sanseverino

Author(s):  
Majid. S. M. Al-Hafidh ◽  
Omar Sh. Al-Yozbaky ◽  
Azhear. S. Al-Fahadi

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