Innovative Smart Grid Solutions for Network Planning and Access

Smart Grids are the cornerstone for Distribution System Operators transformation. Having new solutions to deal with historical and future problems is key to ensure a smooth transition to an advanced power system that not only integrate a large share of renewables and distributed energy resources (e.g. storage, electrical vehicles), but also requires efficient operation, better planning and exceptional customer service. EDP Distribuição is at the forefront of this transformation, as it is developing Inovgrid, a smart grid project in Évora city (Portugal), where a smart grid infrastructure was deployed, and new data is now available to incorporate in planning and access tools and procedures, hence contributing to a Smarter Grid. This paper discusses the results that EDP Distribuição has attained so far in these areas of the smart grid development, as well as the projected evolution of these innovative approaches to the future of the distribution grid, which are being developed in European projects like SuSTAINABLE (www.sustainableproject.eu)

A generalized optimal power flow program for distribution system analysis and operation with distributed energy resources and solid state transformers

The present distribution system is gradually trending towards a smart grid paradigm with massive development of distributed energy resources (DER), advanced power electronics interfaces, and a digitalized communication platform. Such profound changes bring challenges as well as opportunities for an entity like the distribution network operator (DNO) to optimally operate DERs and other controllable elements to achieve higher levels of energy efficiency, economic benefits, supply reliability and power quality. The major contribution of this dissertation is in the development of a generalized three-phase optimal power flow (OPF) program in a novel control scheme for future distribution system optimization and economic operation. It is developed based on primal-dual interior point method (PDIPM). The program is general enough to model comprehensive system components and topologies. The program can also be customized by user-defined cost functions, system constraints, and new device, such as solid state transformers (SST). An energy storage optimal control using dynamic programming is also proposed to coordinate with the OPF based on a pricing signal called the distribution locational marginal price (DLMP). The proposed OPF program can be used by the DNO in an open access competitive control scheme to optimally aggregate the energy mix by combining the profitability of each resource while satisfying system security constraints --Abstract, page iv

Towards Intelligent Distribution Systems: Solutions for Congestion Forecast and Dynamic State Estimation Based Protection

The electrical distribution systems are undergoing drastic changes such as increasing penetration level of distributed renewable energy sources, energy storage, electrification of energy-efficient loads such as heat pumps and electric vehicles, etc., since the last decade, and more changes are expected in the future. These changes pose challenges for the distribution system operators such as increased level of network congestions, voltage variations, as well as protection settings and coordination, etc. These will require the development of new paradigms to operate distribution systems securely, safely, and economically while hosting a large amount of renewable energy sources.First, the thesis proposed a comprehensive assessment framework to assess the distribution system operator’s future-readiness and support them in determining the current status of their network infrastructures, business models, and policies and thus to identify areas for required developments. The analysis for the future-readiness of the three distribution system operators (from France, The Netherlands, and Sweden) using the proposed assessment framework has shown that presently the distribution system operators have a rather small penetration of renewable energy sources in their grids, however, which is expected to increase in the future. The distribution system operators would need investments in flexibilities, novel forecasting techniques, advanced grid control as well as improved protection schemes. The need for the development of new business models for customers and changes in the policy and regulations are also suggested by the analysis. Second, the thesis developed a congestion forecast tool that would support the distribution system operators to forecast and visualize network overloading and voltage variations issues for multiple forecasting horizons ranging from close-to-real time to day-ahead. The tool is based on a probabilistic power flow that incorporates forecasts of production from solar photovoltaic and electricity demand combined with load models along with the consideration of different operating modes of solar photovoltaic inverters to enhance the accuracy. The congestion forecast tool can be integrated into the existing distribution management systems of distribution system operators via an open cross-platform using Codex Smart Edge technology of Atos Worldgrid. The congestion forecast tool has been used in a case study for two real distribution systems (7-bus feeder and 141-bus system). It was demonstrated in the case study that the tool can predict the congestion in the networks with various prediction horizons. The congestion forecast tool would support distribution system operators by forecasting the network congestion and setting up a congestion management plan.Finally, the dynamic state estimation based protection scheme supported by advanced measurement technologies developed within EU project UNITED-GRID has been implemented and validated experimentally at Chalmers power system laboratory. This dynamic state estimation based protection scheme has a strong advantage over the traditional protection scheme as it does not require any relay settings and coordination which can overcome the protection challenges arising in distribution grids with a large amount of renewable energy sources. The results from the validation of the dynamic state estimation based protection scheme at Chalmers laboratory have shown that the fault detection using this scheme has worked properly as expected for an application of the line protection

Real-time thermal state and component loading estimation in active distribution networks

Highly stochastic loading and distributed generation in the emerging active distribution networks means that electric utilities need to deploy intelligent network management tools in order to use their assets to the fullest. Real-Time Thermal Rating (RTTR) provides the possibility for short term and even real-time active distribution network management, enabling the network to run closer to an overload state without damage. In this dissertation, pertinent developments and proposals are presented in three stages on the path towards the development of a real-time monitoring and operation system for active distribution networks. The first stage is the development of distribution network component thermal models for real time implementation. In this dissertation, a numerical model of the air-gap convective heat transfer for underground cable installations inside unfilled conduit is developed. In addition, a dynamic thermal model is developed for prefabricated secondary substation cabins. The most dominant but difficult to solve heat transfer mechanism, natural convection, is modelled by introducing the stack effect principle into the problem. Measurements from a scaled model of prefabricated substations, measurements from actual cabins and 3D Finite Element Method (FEM) simulations are used to validate the numerical model. In the second stage, this dissertation explores the usability of customer level automatic meter reading (AMR) measurements for distribution network state estimation and for load forecasting applications. A method to forecast substation level loads with their respective confidence intervals using hourly AMR metered customer level consumptions is presented. The forecasting and monitoring of a distribution network in real-time can be met with the modeling of classified type load classes. However, it requires careful incorporation of the necessary factors, such as within-group and between-group correlations of customer classes. Binding the aforementioned findings, in the third stage, a framework for day-ahead hour-by-hour thermal state forecasting and thermal ratings of distribution network components is proposed and studied. This work has demonstrated that up to three hours ahead thermal state forecasting of an active distribution network can be achieved with an acceptable level of accuracy. In this dissertation, the benefits and practical implications of the real-time thermal rating are investigated. The introduction of real-time thermal rating in an active distribution network management system enhances the loading capacity significantly compared to static rating. This has been revealed through an increased utilization of installed DGs and through better integration potential of additional DGs