A Coordinate Optimization Model For Solar Photovoltaic Integrated DC Distribution Networks

Abstract:

Solar photovoltaic (PV) systems will drive deep electrification of energy systems leading to clean energy 2050. However, connecting large amounts of solar PV systems on DC networks used in solar farms and possible future DC distribution systems would lead to over voltages and loss of solar PV power output due to voltage issues. Further, solar PV systems integrated into the distribution network operate exclusively to maximize output using maximum power point tracking algorithms, without coordinating with the remainder of the network. This lack of coordination may also lead to reduced solar output due to voltage issues. This thesis presents a coordinated optimization model for solar PV systems and distribution network voltage regulators. The proposed model optimally controls settings of voltage controllers (DC-DC converters), placed at the outputs of solar PV systems and selected distribution lines, while maximizing solar power output and minimizing substation power (i.e. system losses). The solar PV systems are modeled using a trained neural network. The proposed formulation was tested on several systems and compared to an uncoordinated situation. The results obtained demonstrate an increase in solar power of up to 60.06%, in the 28-bus case. The proposed method will be an excellent tool enabling deep electrification using solar PV systems, overcoming limitations of uncoordinated systems.

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