Simulation of Self-Consumption in Small Photovoltaic Panel Energy Application: A Case Study in Estonia

Andres Annuk, Wahiba Yaïci, Vasilij Sudachenko, Peep Miidla

Abstract


Modern residential buildings are often equipped with independent energy sources such as wind generators, PV panels or similar sources from which green energy is generated. Experts predict that prosumers who concurrently produce and consume electricity will soon emerge en masse. Due to fluctuating and intermittent renewable energy sources, this dual process can increase the burden on the electricity grid. In this article, a process simulation of the energy supply of a residential building is developed, with PV panels as the independent source of electricity. The studied parameters of the prosumer nanogrid are a non-shiftable electrical load graph, and a separate load graph of warm water consumption with a battery that ensures the need for energy from the non-shifting load graph. For the annual simulation, we use measurement data with an average interval of 5 minutes. The article models and simulates energy flow graphs that will depend on consumption and production schedules and the size and design of storage devices, such as a buffer battery between the nanogrid and utility grid. One of the outputs of the article is the comparison of the same nanogrid configuration with the wind generator instead of the PV panels as a local energy source. The results show that PV panels require a significantly lower battery and water heater volumes than a wind generator to achieve the same demand cover factor. Compared to the power generation of PV panels with the wind generator, the inverter's power can be reduced to half the capacity without significantly reducing the demand cover


Keywords


Load shifting; energy storage; solar energy; self-consumption; cover factor; nanogrid; battery storage; distributed generation.

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DOI (PDF): https://doi.org/10.20508/ijrer.v11i4.12297.g8818

Data citation

A. Annuk, M. Hovi, J. Kalder, and M. Märss, “Consumption and wind production time-series data,” Estonian University of Life Sciences, Tartu, 2020. https://doi.org/10.15159/eds.dt.20.02 (accessed on the 10th of July 2021).

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