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With the increasing penetration of primarily inertia-less distributed energy resources, allowable delay in the fast frequency reserve provision to ensure marginal stability condition can become comparable with the requisite dead-time for fast-switching in a radial power distribution system (PDS) connected to the transmission system. Consequently, the prevailing short-duration load-generation imbalance might propagate as system-wide frequency excursion in the future power system, which traditionally has not been observed. Furthermore, during the fast-switching, some of the fast-acting reserve (FAR) providing local generators remain inaccessible to the bulk power system (BPS). This work has answered the questions of requisite reserve requirements to cater to such events through efficient energy and FAR provision joint-scheduling. Stochasticity of fast-switching, with temporary faults as a use-case, requires modeling of load-generation imbalance and local resource unavailability, vis-á-vis FAR requirement problem, as a chance-constraint. Due to the limited visibility at the BPS level, PDS operators must ensure sufficient FAR availability for a given confidence level of the chance-constraint. Individual chance-constraints are used to ensure mathematical simplicity. Here, the PDS is operated as a virtual power plant (VPP), where the operator can procure resources locally or from the wholesale market with the aim of profit maximization before the contingency occurs. Results show that FAR requirements can influence the local energy schedule and raise energy costs. Furthermore, the confidence level of the chance-constraint can impact overall profitability, and FAR should be scheduled carefully. Comparative analysis with a modified benchmark IEEE 33-node radial test system and a 98-node test system shows the superior performance of the proposed approach. The impact of the limited available FAR is also demonstrated.

The world is transitioning to utilise distributed generation (DG) to reduce social, economic and environmental effects. As DG penetration increases, determining the associated impacts on distribution networks is vital. This paper proposes a concept around sphere of influence of single and multiple DG units through line current analysis and integrated Sankey and Geospatial visualisation approaches. With the increasing integration of renewable energy sources and the need for grid stability, it becomes imperative to analyse the sphere of influence of DGs in geographic context. The main contribution of the paper is to present the visualisation techniques to determine the sphere of influence of DGs within power networks by considering single and multiple DGs. The proposed study combines the power of Sankey visualisation, a flow diagram technique, with geospatial data to gain insights into the DG sphere. The advantage of the proposed method is it acts as a visual lens to determine DG clusters, flow of power, coherency analysis, voltage support, resource allocation, operational planning, and grid resilience assessment. The proposed method is tested using 33 bus distribution network and visualisation on a representative geospatial map is carried out using Python library and Tableau.

Due to growing concerns related to greenhouse gas emissions, the growing utilization of sustainable energy sources such as photovoltaic (PV) powered electric vehicle (EV) charging stations in the highway transportation sector can be considered as one of the climate change adaptation measures. Reliability and economic considerations are two critical factors that need to be considered in design and operation of PV-powered EV charging stations. This paper develops an approach for the evaluation of reliability for PV-powered charging services. The costs associated with providing reliable services are also assessed. The developed methodology is applied to PV-powered charging stations operating with or without battery energy storage systems (BESS) along a highway to showcase the effect of varying PV system capacity and different inter-station distances on charging service reliability and associated costs. The results demonstrate that the cost-effectiveness of charging stations equipped with BESS becomes increasingly evident as the reliability level improves.

Electric vehicle charging applies a notable strain on the electricity network due to the large load produced. This article will examine these charging loads and their effect on the traditional electricity network using hosting capacity to evaluate this impact. Three indices are proposed to quantitatively describe the hosting capacity. The voltage deviation index describes voltage changes in the network due to variations in loading. The substation power delivery index analyses power flow through a substation as a ratio of its rated capacity to determine its utilisation and if it is overloaded. The current unbalance factor measures phase unbalance in the network using sequence currents. A case study of a distribution network in Australia was performed to examine network capacities and peak loads. A futuristic prediction is made to evaluate how the network will cope with an increase in loads due to electric vehicle charging. Simulations were performed in a series of scenarios including no electric vehicle adoption, adopting electric vehicles as a second vehicles, one electric vehicle per household, and electric vehicle charging with rooftop solar panels. The results showed that the introduction of charging increased voltage sag and power delivery, as indicated by the indices, with some substations experiencing overloading and excessive voltage sag. These issues were mitigated by distributing electric vehicle charging throughout the day and introducing rooftop solar panels. The results of this study can be used to estimate the increase in network capacity required to accommodate for the increase in charging loads.