Luis (Nando) Ochoa


The Future of DER Hosting Capacity and DER Orchestration

Distribution companies, who manage the poles and wires, struggle to have accurate and up-to-date electrical models of their residential areas, known as low voltage (LV) networks. And without electrical models, it is hard to assess how much their networks are capable of hosting distributed energy resources (DER) such as solar PV or electric vehicles; particularly when voltages are likely to be a major issue. Similarly, if distribution companies want to orchestrate/coordinate DER, the calculation of set points or limits (such as operating envelopes) require quantifying the voltage effects from different exports or imports.

Taking advantage of historical smart meter data, this talk will demonstrate that is possible to capture the physics of three-phase LV networks and create an electrical model-free approach to calculate voltages which, in turn, allows the calculation of DER Hosting Capacity and enables DER Orchestration. Using Neural Networks, the nonlinear relationships among the historical data (demand and voltages) and the corresponding LV networks can be captured. This approach can make it possible for distribution companies to bypass the time-consuming process of producing LV network models and, instead, carry out accurate, extremely fast voltage calculations for any type of what-if scenarios involving residential solar PV, batteries, electric vehicles, etc.

Managing EVs in Urban and Rural Grids

The adoption of electric vehicles (EVs) poses technical and economic challenges for our power grid. Electricity distribution networks were not designed with a high penetration of electric vehicles in mind. Charging EVs at home can significantly increase our normal demand, affecting the poles and wires. Nonetheless, if EV charging is managed well, it could mean more efficient networks, leading to lower prices and better outcomes for energy consumers.

Mitigating the effects of mass EV integration into existing power systems is a complex but not impossible task. However, whether it is by directly managing the EV charging points or by persuading EV users to charge at different times, it is important for distribution companies to understand the extent of the benefits of potential EV management solutions.

This talk will present the results from studies that simulate the control of EV charging points at homes as well as the use of time-of-use tariffs in both urban and rural areas. The studies were carried out as part of the project “EV Integration” funded by Energy Networks Australia (ENA) and the Centre for New Energy Technologies (C4NET). The assessment involves fully modelled HV (22kV and 11kV) feeders, and pseudo low voltage (0.4kV) networks to capture the effects close to end users, time-series analyses, and rapid adoption of EVs.

Quantifying the DER Hosting Capacity of Distribution Networks: Models, Considerations and Tools

Distribution companies all over the world are finding it challenging to quantify the ability of their existing low and medium voltage networks to host residential Distributed Energy Resources (DER), such as photovoltaic (PV) systems and electric vehicles (EVs). This quantification, known as Hosting Capacity, is also needed to assess different potential solutions that could increase DER uptake. Thus, it is crucial for distribution companies to carry out adequate DER hosting capacity quantifications using appropriate models, considerations, and tools.

This half-day tutorial will present and discuss different aspects required to quantify the residential DER hosting capacity of distribution networks, particularly focusing on solar PV and EVs. Using realistic case studies from urban and rural integrated MV-LV networks from Australia, this tutorial will explain and demonstrate the benefits but also the potential challenges and limitations of exploiting existing assets as well as the capabilities of DER.

Part 1: Distribution Networks and DER
Part 2: PV Hosting Capacity (PV Inverters and Batteries)
Part 3: EV Hosting Capacity (EV Management and Time-of-Use Tariffs)

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