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Energy management of grid connected rooftop solar system with battery storage

机译:带电池储能的并网屋顶太阳能系统的能源管理

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Shift of the focus from bulk generation to distributed generation is an established global trend in the power sector. Further the mode of distributed generations is shifting from dependence on fossil fuels to renewable sources. These sources are intermittent in nature and their generation pattern does not match the load pattern there by creating a need for a battery storage system. In this context, energy management presents itself as inevitable challenge in operating a grid connected distributed renewable sources. The challenge is due to factors such as intermittency of source, time of the day prices, sizing of solar panels and battery, limitations of charging and discharging rates of the battery. To address these, in this paper, an algorithm for energy management of grid-connected rooftop solar with battery storage is proposed. The objective is to maximize the savings in electricity bill by decreasing the power drawn from the grid during high grid prices. The charge controller of battery uses this algorithm for making decision on charging or discharging of the battery or keeping it in idle mode. The algorithm is coded in MATLAB and tested with realistic demand patterns and solar generation patterns of data representing a duration of 30 days. The obtained results show effective savings on electricity bill monthly. The optimal selection of number of solar panels, battery size has also been presented. The proposed algorithm helps in effectively deriving the potential benefits of grid connected rooftop solar system with battery storage.
机译:将重点从散装发电转移到分布式发电是电力行业的既定全球趋势。此外,分布式发电的模式正在从对化石燃料的依赖转变为可再生资源。这些源本质上是断续的,并且通过产生对电池存储系统的需求,它们的产生模式与那里的负载模式不匹配。在这种情况下,能源管理本身就是运行连接分布式可再生能源的电网时不可避免的挑战。面临的挑战是由于以下因素引起的,例如电源的间歇性,一天中的时间价格,太阳能电池板和电池的尺寸,电池的充电和放电速率的限制。针对这些问题,本文提出了一种带电池储能的并网屋顶太阳能的能量管理算法。目的是通过在高电网价格期间减少从电网获得的电力来最大程度地节省电费。电池的充电控制器使用此算法来确定电池的充电或放电或使其处于空闲模式。该算法在MATLAB中进行了编码,并通过代表30天持续时间的实际需求模式和太阳能发电模式进行了测试。获得的结果表明每月可以有效节省电费。还提出了太阳能电池板数量,电池尺寸的最佳选择。所提出的算法有助于有效地推导带有电池储能的并网屋顶太阳能系统的潜在利益。

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