Iet Generation Transmission & Distribution
Institution of Engineering and Technology
About: Iet Generation Transmission & Distribution is an academic journal. The journal publishes majorly in the area(s): Electric power system & AC power. It has an ISSN identifier of 1751-8687. It is also open access. Over the lifetime, 4449 publications have been published receiving 83124 citations.
Papers published on a yearly basis
TL;DR: In this paper, a smart load management (SLM) approach for the coordination of multiple plug-in electric vehicle (PEV) chargers in distribution feeders is proposed.
Abstract: New smart load management (SLM) approach for the coordination of multiple plug-in electric vehicle (PEV) chargers in distribution feeders is proposed. PEVs are growing in popularity as a low emission and efficient mode of transport against petroleum-based vehicles. PEV chargers represent sizeable and unpredictable loads, which can detrimentally impact the performance of distribution grids. Utilities are concerned about the potential overloads, stresses, voltage deviations and power losses that may occur in distribution systems from domestic PEV charging activity as well as from newly emerging charging stations. Therefore this study proposes a new SLM control strategy for coordinating PEV charging based on peak demand shaving, improving voltage profile and minimising power losses. Furthermore, the developed SLM approach takes into consideration the PEV owner preferred charging time zones based on a priority selection scheme. The impact of PEV charging stations and typical daily residential loading patterns are also considered. Simulation results are presented to demonstrate the significant performance improvement offered by SLM for a 1200 node test system topology consisting of several low-voltage residential networks populated with PEVs.
TL;DR: This study proposes a secondary voltage and frequency control scheme based on the distributed cooperative control of multi-agent systems that is fully distributed such that each distributed generator only requires its own information and the information of its neighbours on the communication digraph.
Abstract: This study proposes a secondary voltage and frequency control scheme based on the distributed cooperative control of multi-agent systems. The proposed secondary control is implemented through a communication network with one-way communication links. The required communication network is modelled by a directed graph (digraph). The proposed secondary control is fully distributed such that each distributed generator only requires its own information and the information of its neighbours on the communication digraph. Thus, the requirements for a central controller and complex communication network are obviated, and the system reliability is improved. The simulation results verify the effectiveness of the proposed secondary control for a microgrid test system.
TL;DR: In this article, a probabilistic power flow model that takes into account spatially correlated power sources and loads is proposed to assess the impact of intermittent generators such as wind power ones on a power network.
Abstract: A probabilistic power flow model that takes into account spatially correlated power sources and loads is proposed. It is particularly appropriate to assess the impact of intermittent generators such as wind power ones on a power network. The proposed model is solved using an extended point estimate method that accounts for dependencies among the input random variables (i.e. loads and power sources). The proposed probabilistic power flow model is illustrated through 24-bus and 118-bus case studies. Finally, conclusions are duly drawn.
TL;DR: In this article, a multi-objective index-based approach is proposed to optimally determine the size and location of multi-distributed generation (DG) units in distribution system with non-unity power factor considering different load models.
Abstract: This study proposes a multi-objective index-based approach to optimally determine the size and location of multi-distributed generation (DG) units in distribution system with non-unity power factor considering different load models. It is shown that load models can significantly affect the optimal location and sizing of DG resources in distribution systems. The proposed multi-objective function to be optimised includes a short-circuit-level parameter to represent the protective device requirements. The proposed function also considers a wide range of technical issues such as active and reactive power losses of the system, the voltage profile, the line loading and the Mega Volt Ampere (MVA) intake by the grid. The optimisation technique based on particle swarm optimisation is introduced. The analysis of continuation power flow to determine the effect of DG units on the most sensitive buses to voltage collapse is carried out. The proposed algorithm is tested using the 38-bus radial system and the IEEE 30-bus meshed system. The results show the effectiveness of the proposed algorithm.
TL;DR: In this article, the unscented Kalman filter (UKF) is proposed for power system dynamic state estimation, which is based on the application of the Unscented Transformation (UT) combined with the Kalman Filter theory.
Abstract: A new estimation method for power system dynamic state estimation, the unscented Kalman filter (UKF), is presented. It is based on the application of the unscented transformation (UT) combined with the Kalman filter theory. One of the challenges in the process of power system estimation is coping with a highly non-linear mathematical model of network equations, which is usually approximated through a linearisation. The new derivative free estimation method overcomes this limitation using the UT and achieves better accuracy with simpler implementation. The UKF is derived and demonstrated using three different test power systems under typical network and measurement conditions. Its performance is compared with the classical extended Kalman filter. The simplicity of the new estimator and its low computational demand make it a better option to be applied in the next generation of dynamic system estimators.
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