{"title":"Full Shading for Photovoltaic Systems Operating under Snow Conditions","authors":"Farhad Khosrojerdi, S. Gagnon, Raul Valverde","doi":"10.1109/SEGE52446.2021.9534991","DOIUrl":null,"url":null,"abstract":"Photovoltaic (PV) installers and non-technical solar energy consumers use PV planning software for the system design and simulation. End-users rely on the designed system and power estimations provided by these tools. However, most planning software products fail to consider shading conditions. This problem affects energy forecasting for solar power plants located in cold climates. In this paper, we define the status of full shading for a snow-covered panel and the minimum depth of snow creating it. Using a case study, we design the project by the most reliable planning software, System Advisor Model (SAM). We show that the simulation overestimates power generations for snowy months. To identify shading conditions and the correlated performance reductions, we compare the SAM results with the measured data collected onsite. As a result, the minimum depth of snow that can create full shading and zero production is detected. Moreover, comparing the measured data with the simulated power helps us to define a rule-base system providing PV performance reduction factors. It assists solar sector practitioners to plan a PV project accurately, especially for the locations where snowfall is an important environmental factor for several months.","PeriodicalId":438266,"journal":{"name":"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEGE52446.2021.9534991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Photovoltaic (PV) installers and non-technical solar energy consumers use PV planning software for the system design and simulation. End-users rely on the designed system and power estimations provided by these tools. However, most planning software products fail to consider shading conditions. This problem affects energy forecasting for solar power plants located in cold climates. In this paper, we define the status of full shading for a snow-covered panel and the minimum depth of snow creating it. Using a case study, we design the project by the most reliable planning software, System Advisor Model (SAM). We show that the simulation overestimates power generations for snowy months. To identify shading conditions and the correlated performance reductions, we compare the SAM results with the measured data collected onsite. As a result, the minimum depth of snow that can create full shading and zero production is detected. Moreover, comparing the measured data with the simulated power helps us to define a rule-base system providing PV performance reduction factors. It assists solar sector practitioners to plan a PV project accurately, especially for the locations where snowfall is an important environmental factor for several months.
光伏(PV)安装人员和非技术太阳能消费者使用PV规划软件进行系统设计和仿真。最终用户依赖于这些工具提供的设计系统和功率估计。然而,大多数规划软件产品没有考虑遮阳条件。这一问题影响了位于寒冷气候地区的太阳能发电厂的能量预测。在本文中,我们定义了一个被雪覆盖的面板的完全遮阳状态和创建它的最小积雪深度。通过案例研究,我们使用最可靠的规划软件System Advisor Model (SAM)来设计项目。结果表明,该模拟高估了积雪月份的发电量。为了确定遮阳条件和相关的性能下降,我们将SAM结果与现场收集的测量数据进行了比较。因此,可以创建完全遮阳和零生产的最小积雪深度被检测到。此外,将实测数据与模拟功率进行比较有助于我们定义一个提供光伏性能降低因子的基于规则的系统。它帮助太阳能行业从业者准确地规划光伏项目,特别是对于几个月来降雪是重要环境因素的地方。