Utility-scale and small scale wind and solar power installations along with electric vehicle charging stations, and other active sources of energy are increasing at the medium and lower voltage levels in the distribution grid. This situation requires a better understanding of the impact of high penetration of weather-dependent renewable energy sources on the operating conditions of the distribution network at both medium and low voltage levels. Despite the need, a multi-voltage level distribution network model, based on real network data and weather-dependent renewable generation data, has not been presented for distribution grid studies. This paper presents a comprehensive multi-voltage level active distribution network model based on real network data along with load and generation time-series for about a year. The network topology is modelled based on geographical data for various rural, semi-urban, and urban locations. The distribution network is embodied with a large share of renewable generation sources, with generation time-series simulated from meteorological data. The network is also flexible to incorporate other assets such as electric vehicle charging stations, storage, etc. The presented active distribution network model can be used to study, optimize, and control the effects of weather-dependent generation and other network assets in the distribution grid.
<div>Utility-scale and small scale wind and solar power installations along with electric vehicle charging stations, and other active sources of energy are increasing at the medium and lower voltage levels in the distribution grid. This situation required a better understanding of the impact of high penetration of weather-dependent renewable energy sources on the operating conditions of the distribution network at both medium and low voltage levels. Despite the need, a multi-voltage level distribution network model, based on real network data and weather-dependent renewable generation data, has not been presented for distribution grid studies. This paper presents a comprehensive multi-voltage level active distribution network model based on real network data along with load and generation time-series for about a year. The network topology is modelled based on geographical data for various rural, semi-urban, and urban locations. The distribution network is embodied with a large share of renewable generation sources, with generation time-series simulated from meteorological data. The network is also flexible to incorporate other assets such as electric vehicle charging stations, storage, etc. Thus, the presented active distribution network model can be used to study, optimize, and control the effects of weather dependent generation and other network assets in the distribution grid.</div>
<div>The increased penetration of wind power plants (WPPs) in distribution networks challenges the distribution system operators (DSOs) to improve and optimize networks’ operation. A higher amount of local power production translates to more losses in the network. This paper proposes a deterministic optimization methodology to minimize the losses in distribution networks with WPPs, by exploiting WPPs’ capability to control reactive power in coordination with the on-load tap changers from the MV/HV transformer, avoiding the need for network reinforcements. The principal objective is to optimize the reactive power flow in the network. Measurements from a real distribution network with a large share of controllable WPPs under varying wind and load conditions are used for the study. The benefits and the challenges of the optimization methodology are assessed and discussed with respect to active power losses, voltage profile and reactive power. The results show that with reactive power support from WPPs, network losses are reduced by 4.2 %. Higher loss reductions (up to 19 %) can be achieved through a coordinated action between the WPPs and TSO. Furthermore, it is shown that the distribution network can act as an asset to the transmission network for reactive power support, via actively controlling WPP’s reactive power.</div>
<div>The increased penetration of wind power plants (WPPs) in distribution networks challenges the distribution system operators (DSOs) to improve and optimize networks’ operation. A higher amount of local power production translates to more losses in the network. This paper proposes a deterministic optimization methodology to minimize the losses in distribution networks with WPPs, by exploiting WPPs’ capability to control reactive power in coordination with the on-load tap changers from the MV/HV transformer, avoiding the need for network reinforcements. The principal objective is to optimize the reactive power flow in the network. Measurements from a real distribution network with a large share of controllable WPPs under varying wind and load conditions are used for the study. The benefits and the challenges of the optimization methodology are assessed and discussed with respect to active power losses, voltage profile and reactive power. The results show that with reactive power support from WPPs, network losses are reduced by 4.2 %. Higher loss reductions (up to 19 %) can be achieved through a coordinated action between the WPPs and TSO. Furthermore, it is shown that the distribution network can act as an asset to the transmission network for reactive power support, via actively controlling WPP’s reactive power.</div>
<div>Utility-scale and small scale wind and solar power installations along with electric vehicle charging stations, and other active sources of energy are increasing at the medium and lower voltage levels in the distribution grid. This situation required a better understanding of the impact of high penetration of weather-dependent renewable energy sources on the operating conditions of the distribution network at both medium and low voltage levels. Despite the need, a multi-voltage level distribution network model, based on real network data and weather-dependent renewable generation data, has not been presented for distribution grid studies. This paper presents a comprehensive multi-voltage level active distribution network model based on real network data along with load and generation time-series for about a year. The network topology is modelled based on geographical data for various rural, semi-urban, and urban locations. The distribution network is embodied with a large share of renewable generation sources, with generation time-series simulated from meteorological data. The network is also flexible to incorporate other assets such as electric vehicle charging stations, storage, etc. Thus, the presented active distribution network model can be used to study, optimize, and control the effects of weather dependent generation and other network assets in the distribution grid.</div>
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