# An Algorithm for Estimation of SF\({}_{6}\) Leakage on Power Substation Assets
## 1 Introduction  
In the last two decades, environmental regulations and protocols signed by a great part of the international community, such as the United Nation's Kyoto [1] and Paris agreements [2], led Distribution System Operators (DSOs) and Transmission System Operators (TSOs) to contribute to reducing their carbon footprint [3]. Some power industry companies have already started to estimate their environmental impact in order to include environmental risk assessment as a strategic objective [4]. A way to mitigate those risks, minimize costs, and maximize performance is to implement an asset management system [5], taking into account that an adequate process to estimate environmental impact is needed. Sulfur hexafluoride (SF\({}_{6}\)) has outstanding dielectric properties, with about 2.5 times the dielectric strength of air under the same conditions. SF\({}_{6}\) has a low dissociation temperature and high dissociation energy, which makes it an excellent arc quenching gas. Those characteristics led switchgear manufacturers to use it to design their equipment [6]. However, according to EU regulations, SF\({}_{6}\) has a global warming potential (GWP) that is 22,800 times greater than that of carbon dioxide (CO\({}_{2}\)) [7]. It also has a lifetime in the atmosphere of 3200 years relative to CO\({}_{2}\)[8]. Aware of this environmental impact, The European Union (EU) is reviewing its fluorinated greenhouse gases regulation, which include SF\({}_{6}\), in order to reduce its emissions by two-thirds compared to 2014 levels by 2030 [9]. The EU goal is to be climate-neutral by 2050 [10], which is why the European Network of Transmission System Operators for Electricity (ENTSO-E) is willing to commit to reducing annual SF\({}_{6}\) emissions for the existing fleet below 0.5% of the installed SF\({}_{6}\) in 2019. New equipment will tend to be SF\({}_{6}\) free or have very low GWP by 2050 [11]. According to [12], only 0.1% of human-made global warming in 2006 was related to SF\({}_{6}\) emissions, of which around 10% was due to the electric industry. A study from Reseau de Transport d'Electricite (RTE), the transmission system operator of France, showed that its SF\({}_{6}\) releases reached seven tons in 2008. The calculated valuation was EUR 16.8 million,using a penalty value of EUR 100 per ton of CO\({}_{2}\)[13]. The same company stated that in 2018 its SF\({}_{6}\) emissions were equivalent to 138,400 tons of CO\({}_{2}\), representing 13% of total RTE emissions [14]. Potential sources of SF\({}_{6}\) emissions appear from leakage in SF\({}_{6}\)-containing equipment and losses during equipment installation, maintenance, and decommissioning [15]. Studies that estimate SF\({}_{6}\) leakage in electrical equipment can be found in the literature. In [16], surveys are used to gather information about top-up operations in SF\({}_{6}\) circuit breakers, resulting in lower and upper bound weighted-average leak rates. Another work studied the influence of temperature on SF\({}_{6}\) leakage in switchgear, giving a lifetime estimation of the analyzed equipment [17]. In order to support decision-making processes, a mixed approach is necessary using the available information of the current fleet and a proper, yet simple, model to estimate the impact of future projects. This paper proposes an algorithm to evaluate the current state of power substation assets and to estimate SF\({}_{6}\) leakage on forthcoming projects. Its main objective is to facilitate management of assets and the general decision-making process. On one hand, the algorithm employs existing fleet data in order to produce straightforward charts that summarize the current state of SF\({}_{6}\)-containing assets. On the other hand, it allows setting a group of parameters into a simple model for a quick SF\({}_{6}\) leakage projection on future projects. The structure of this work is composed of three sections. The second section presents the algorithm, including the description of each stage.