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Economic decision-making tool for distributed solar photovoltaic panels and storage: The case of Chile
摘要： The benefits of distributed solar photovoltaic (PV) panels and storage have been widely reported in the literature. However, the economic impact on the electricity bill due to its implementation is generally unknown by the distribution customers. In this work, we develop an economic decision-making tool for the case of Chile. This tool is based on an easy-to-implement algorithm, which computes the number of solar PV panels and batteries that maximize the economic return in a given time horizon subject to several technical constraints. To illustrative the usefulness of our tool, a personal computer implementation and a numerical example are considered. The obtained results compute the economic benefit in net present value of the best alternative solar PV panels and batteries in an execution time less than 30 seconds.
关键词： Distributed solar photovoltaic panels and storage,Economic analysis,Economic decision-making tool
更新于2025-09-12 10:27:22
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New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes
摘要： The development of perpetually powered sensor networks for environment monitoring to avoid periodic battery replacement and to ensure the network never goes offline due to power is one of the primary goals in sensor network design. In many environment-monitoring applications, the sensor network is internet-connected, making the energy budget high because data must be transmitted regularly to a server through an uplink device. Determining the optimal solar panel size that will deliver sufficient energy to the sensor network in a given period is therefore of primary importance. The traditional technique of sizing solar photovoltaic (PV) panels is based on balancing the solar panel power rating and expected hours of radiation in a given area with the load wattage and hours of use. However, factors like the azimuth and tilt angles of alignment, operating temperature, dust accumulation, intermittent sunshine and seasonal effects influencing the duration of maximum radiation in a day all reduce the expected power output and cause this technique to greatly underestimate the required solar panel size. The majority of these factors are outside the scope of human control and must be therefore be budgeted for using an error factor. Determining of the magnitude of the error factor to use is crucial to prevent not only undersizing the panel, but also to prevent oversizing which will increase the cost of operationalizing the sensor network. But modeling error factors when there are many parameters to consider is not trivial. Equally importantly, the concept of microclimate may cause any two nodes of similar specifications to have very different power performance when located in the same climatological zone. There is then a need to change the solar panel sizing philosophy for these systems. This paper proposed the use of actual observed solar radiation and battery state of charge data in a realistic WSN-based automatic weather station in an outdoor uncontrolled environment. We then develop two mathematical models that can be used to determine the required minimum solar PV wattage that will ensure that the battery stays above a given threshold given the weather patterns of the area. The predicted and observed battery state of charge values have correlations of 0.844 and 0.935 and exhibit Root Mean Square Errors of 9.2% and 1.7% for the discrete calculus model and the transfer function estimation (TFE) model respectively. The results show that the models perform very well in state of charge prediction and subsequent determination of ideal solar panel rating for sensor networks used in environment monitoring applications.
关键词： battery state of charge,environment monitoring,solar radiation,discrete calculus model,transfer function estimation,solar photovoltaic panels,sensor nodes
更新于2025-09-11 14:15:04