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

Quasi-Dynamic Analysis of a Local Distribution System with Distributed Generation. Study Case: The IEEE 13 Node System

La generación distribuida es una de las estrategias más aceptadas para atender el aumento de la demanda de electricidad a nivel mundial. Desde el año 2014 las entidades gubernamentales en Colombia han emitido leyes y resoluciones para promover y regular la entrada en operación de diferentes tecnologías de generación, en el sistema eléctrico del país. Incorporar sistemas de generación distribuida en redes de distribución convencionales puede traer consigo problemas si previamente no se realizan los estudios que permitan determinar las consecuencias de la entrada en operación de estas nuevas tecnologías de generación. Este panorama representa un nuevo desafío para los operadores de las redes de distribución, ya que deben garantizar que los sistemas que administran puedan integrar estas nuevas fuentes de generación, sin afectar el correcto funcionamiento de la red eléctrica. En este artículo se modifica el sistema IEEE de 13 nodos incorporando las curvas de carga de los tres tipos de consumidores del sector eléctrico colombiano en las cargas del modelo y se integran sistemas de generación distribuida a partir de fuentes no convencionales de energía a dos nodos del sistema, con el objetivo de hacer un análisis cuasi-dinámico de las diferentes variables eléctricas que permitan determinar qué impacto tienen estas nuevas tecnologías en un sistema de distribución local. Como resultado, los perfiles de voltaje y potencia activa/reactiva no muestran cambios considerables en el comportamiento de la red eléctrica, pero sí se observa que, en los escenarios de simulación donde opera la generación distribuida, el sistema tiende a un aumento considerable en las corrientes y pérdidas presentes en las líneas. Así, se concluye que existen dos alternativas para no tener inconvenientes con la operación de los nuevos nodos con generación distribuida: operar de manera aislada esa parte del sistema o reforzar la red de distribución local a través de la implementación de nuevas líneas de distribución en el sistema.Distributed generation is one of the most accepted strategies to attend the increase in electrical demand around the world. Since 2014, Colombian government agencies have enacted laws and resolutions to promote and regulate the introduction of different generation technologies into the country’s electrical system. The incorporation of distributed generation systems into conventional distribution networks can cause problems if technical studies are not previously carried out to determine the consequences of the start of the operations of these new generation technologies. This scenario represents a new challenge for distribution networks operators because they must ensure that their systems can integrate these new generation sources without affecting the correct operation of the grid. In this article, the IEEE 13 nodes system is modified by incorporating the load curves of the three types of consumers in the Colombian electricity market into the model. Additionally, distributed generation systems from non-conventional sources of energy are integrated into two system nodes in order to perform a quasi-dynamic analysis of the different electrical variables, which can be used to determine the impact of these new technologies on a local distribution system. The voltage profiles and active and reactive power do not show considerable changes in the behavior of the electrical network; however, in the simulation scenarios where distributed generators are operating, the system exhibits a considerable increase in lines losses. There are two alternatives to manage these unusual levels in the operation of the nodes with distributed generation: (1) operating these new DG nodes in islanded mode or (2) strengthening the local distribution system through the implementation of new distribution lines in the network

Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid

Recently there has been increasing interest in improving smart grids efficiency using computational intelligence. A key challenge in future smart grid is designing Optimal Power Flow tool to solve important planning problems including optimal DG capacities. Although, a number of OPF tools exists for balanced networks there is a lack of research for unbalanced multi-phase distribution networks. In this paper, a new OPF technique has been proposed for the DG capacity planning of a smart grid. During the formulation of the proposed algorithm, multi-phase power distribution system is considered which has unbalanced loadings, voltage control and reactive power compensation devices. The proposed algorithm is built upon a co-simulation framework that optimizes the objective by adapting a constriction factor Particle Swarm optimization. The proposed multi-phase OPF technique is validated using IEEE 8500-node benchmark distribution system.Comment: IEEE PES GM 2014, Washington DC, US

Measurements, Models, Systems and Design

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Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems

In this paper, we consider a cognitive multi-hop relay secondary user (SU) system sharing the spectrum with some primary users (PU). The transmit power as well as the hop selection of the cognitive relays can be dynamically adapted according to the local (and causal) knowledge of the instantaneous channel state information (CSI) in the multi-hop SU system. We shall determine a low complexity, decentralized algorithm to maximize the average end-to-end throughput of the SU system with dynamic spatial reuse. The problem is challenging due to the decentralized requirement as well as the causality constraint on the knowledge of CSI. Furthermore, the problem belongs to the class of stochastic Network Utility Maximization (NUM) problems which is quite challenging. We exploit the time-scale difference between the PU activity and the CSI fluctuations and decompose the problem into a master problem and subproblems. We derive an asymptotically optimal low complexity solution using divide-and-conquer and illustrate that significant performance gain can be obtained through dynamic hop selection and power control. The worst case complexity and memory requirement of the proposed algorithm is O(M^2) and O(M^3) respectively, where $M$ is the number of SUs