pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems

pandapower is a Python based, BSD-licensed power system analysis tool aimed at automation of static and quasi-static analysis and optimization of balanced power systems. It provides power flow, optimal power flow, state estimation, topological graph searches and short circuit calculations according to IEC 60909. pandapower includes a Newton-Raphson power flow solver formerly based on PYPOWER, which has been accelerated with just-in-time compilation. Additional enhancements to the solver include the capability to model constant current loads, grids with multiple reference nodes and a connectivity check. The pandapower network model is based on electric elements, such as lines, two and three-winding transformers or ideal switches. All elements can be defined with nameplate parameters and are internally processed with equivalent circuit models, which have been validated against industry standard software tools. The tabular data structure used to define networks is based on the Python library pandas, which allows comfortable handling of input and output parameters. The implementation in Python makes pandapower easy to use and allows comfortable extension with third-party libraries. pandapower has been successfully applied in several grid studies as well as for educational purposes. A comprehensive, publicly available case-study demonstrates a possible application of pandapower in an automated time series calculation

The Energy Stream Analysis Method for Integrated Energy Systems

This research presents a novel method for analyzing energy flows in integrated energy systems (IES) using a likelihood-based approach. The proposed method incorporates the concept of Probabilistic Load Flow (PLF) from power systems into the analysis of IES likelihood energy flow points. By assessing the qualitative impact of uncertainties on the probability distribution of the state quantities in integrated energy systems encompassing electricity, air, and heat, this method enables a comprehensive evaluation of the load and output of wind electric fields. The outcomes of this research contribute to establishing a solid foundation for real-time network planning, steady-state analysis, optimized operation, control, and safety analysis of integrated energy systems

Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education

Gym-ANM is a Python package that facilitates the design of reinforcement learning (RL) environments that model active network management (ANM) tasks in electricity networks. Here, we describe how to implement new environments and how to write code to interact with pre-existing ones. We also provide an overview of ANM6-Easy, an environment designed to highlight common ANM challenges. Finally, we discuss the potential impact of Gym-ANM on the scientific community, both in terms of research and education. We hope this package will facilitate collaboration between the power system and RL communities in the search for algorithms to control future energy systems.Comment: 5 pages, 2 figures, 2 code sample

DiME and AGVIS A Distributed Messaging Environment and Geographical Visualizer for Large-scale Power System Simulation

This paper introduces the messaging environment and the geographical visualization tool of the CURENT Large-scale Testbed (LTB) that can be used for large-scale power system closed-loop simulation. First, Distributed Messaging Environment (DiME) implements an asynchronous shared workspace to enable high-concurrent data exchange. Second, Another Grid Visualizer (AGVis) is presented as a geovisualization tool that facilitates the visualization of real-time power system simulation. Third, case studies show the use of DiME and AGVis. The results demonstrate that, with the modular structure, the LTB is capable of not only federal use for real-time, large-scale power system simulation, but also independent use for customized power system research.Comment: 5 pages, 7 figures, conferenc

Simulación de cortocircuitos en sistemas eléctricos de potencia usando métodos tradicionales y normativas

El cálculo de cortocircuitos es una tarea fundamental en los sistemas eléctricos de potencia, ya con esta información se puede dimensionar equipos, además de ajustar el desempeño de las protecciones eléctricas, evitar los fenómenos transitorios. Desde el punto de vista académico, los softwares no suelen ser amigables con el usuario y no entregan toda la información del proceso de cálculo. Con este antecedente, en este trabajo se desarrolla los modelos de cálculos de cortocircuito según los métodos IEC 60909 y Completo. Estas dos metodologías son implementadas en Matlab y comprobados con el software Power World a fin de obtener una codificación que permita evaluar cortocircuitos en cualquier sistema de potencia. Se emplea dos sistemas de prueba el primer sistema encontrado en la literatura para el cálculo de cortocircuitos y el segundo sistema de prueba propuesto por IEEE. Por tanto, los resultados obtenidos aseguran una respuesta adecuada y en cuanto al método de sistematización dispuesto, brinda primacías computacionales y ha inspeccionado resultados de forma rápida y representativa.Short-circuit calculation is a fundamental task in electrical power systems, because with this information you can size equipment, in addition to adjusting the performance of electrical protections, avoid transient phenomena. From an academic point of view, software is not usually user-friendly and does not deliver all the information from the calculation process. With this background, this work develops the short-circuit calculation models according to IEC 60909 and Complete methods. These two methodologies are implemented in Matlab and tested with Power World software to obtain a coding that allows to evaluate short circuits in any power system. Two test systems are used the first system found in the literature for short-circuit calculation and the second test system proposed by IEEE. Therefore, the results obtained ensure an adequate response and in terms of the method of systematization provided, provides computational primacies, and has inspected results quickly and representatively

Comparison Between Ring and Radial Configurations of the University of Trieste Campus MV Distribution Grid

Distribution systems are being pushed towards smarter architectures, management strategies, and controls. To develop new platforms and algorithms for distribution systems management, the University of Trieste is using its medium voltage MW-scale ring distribution system as a demonstrator. In addition to the installation of a real-time monitoring system, power system studies and analyses are required. The paper presents and compares some results concerning the power system operation in both closed (normal operation) and open (post fault operation) configurations, where the latter are identified by means of a quantitative dependability analysis. In particular, the voltage profile, the currents, and the losses in the system are studied, evaluating the impact of faults capable of opening the ring

An enhanced virtual power plant for flexibility services into a local area (including EV's)

Aggregation by Virtual Power Plants to provide flexibility to distribution and transmission networks is seen as an important element in the transition to Net-zero. This paper presents work carried out in the SIES 2022 ERA-Net project, which is investigating in detail the possible provision of flexibility by different technologies, including EVs, but thorough a lens of different business models. Thus, presented work relies on the real use cases. The focus of this work is on the construction of grid representations to guide bidding in potential flexibility markets. It shows that without an appropriate level of detail on the wider grid connections, these bidding strategies, and therefore associated asset optimization schedules, could lead to errors. A methodology that derives EV price response curves is highlighted, with an aim to use such curves in sophisticated optimization scheduling module for further work in management of EV integration

Multi-layered simulation platform for future worlds distribution system scenarios

With the current Distribution System Operator (DSO) transition, DSOs are looking for novel cost-effective solutions to manage distribution networks. To avoid operational failures these solutions must be evaluated in a realistic end to end test environment prior to deployment. To meet this requirement PNDC is presently developing a platform that integrates solutions for power system analysis, market modelling, and real-time simulation. This multi-layered simulation platform will be used to investigate the impact of different DSO operational scenarios (e.g. flexibility procurement, communication interfaces, and vendor provided solutions). To develop the case study presented in this paper aspects of the Open Networks ‘Future Worlds’ were utilised. The ‘Future Worlds’ were developed by the UK Energy Networks Association and represent potential scenarios for the UK future electricity industry structure. This paper presents a case study using the PNDC platform. This case study reflects ‘Future World’ A and simulates an enforced power exchange profile at a grid supply point. In the case study a controllable demand is simulated in real-time and interfaces with power flow analysis and an optimal flexibility procurement algorithm. The case study demonstrates the capability of the multi-layered platform to manage network limitations by procuring flexibility services within a simulated distribution network