Abstract
The increasing penetration of photovoltaic (PV) power generation into the distribution grids has resulted in frequent reverse active power flows, rapid fluctuations in voltage magnitudes, and power loss. To overcome these challenges, this paper identifies the resource management of grid-connected PV systems with active and reactive power injection capabilities using smart inverters. This approach is aimed to minimize the voltage deviations and power losses in the grid-connected systems to accommodate the high penetration of PV systems. A kernel-based approach is proposed to learn policies and evaluate the reactive power injections with smart inverters for improving grid profile, minimizing power losses, and maintaining safe operating voltage limits. The proposed approach performs inverter coordination through nonlinear control policies using anticipated scenarios for load and generation. To assess the performance of the proposed approach, numerical simulations are performed with a single-phase grid-connected PV system connected to an IEEE bus system. The results show the effectiveness of the proposed approach in minimizing power losses and achieving a good voltage regulation.
Highlights
Photovoltaics (PV) is considered as a logical solution to handle the drawbacks in conventional generation resources due to their local availability, falling prices, and sustainability
This paper developed a kernel-based reactive power control approach to achieve resource management and mitigating the impacts of varying loads and high PV penetrations in the distribution grid
The policies have been designed to evaluate the control set-points for different scenarios and estimation has been done for the reactive power control in real-time using inputs and outputs individually
Summary
Photovoltaics (PV) is considered as a logical solution to handle the drawbacks in conventional generation resources due to their local availability, falling prices, and sustainability. The PV generation and instantaneous loads from any node in a typical distribution grid setup are communicated to a central utility controller [18] This controller computes the reactive power injection set-points and communicates them to the inverters at different nodes to minimize the ohmic losses subject to voltage regulation constraints. The significance of sparse control is to jointly learn the inverter rules by posing the optimal power flow problem as a multi-function learning task This is considered as a resourceful representation of inverter control development as it saves the requirement for communication elements. In light of these issues, this paper proposes a mapping of reactive power control approaches as linear or nonlinear policies concerning their input features.
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