Power-flow study

About: Power-flow study is a research topic. Over the lifetime, 8091 publications have been published within this topic receiving 155053 citations. The topic is also known as: load-flow study.

Direct Construction of Optimal Generation Mix

Abstract: A model has been developed for planning the generation mix of a power system at some target year. This optimal target mix algorithm extends the classical screening curves approach to recognize capacity constraints on existing units and it utilizes the mathematical properties of the optimal solution to recursively construct the generation mix. Not only is the method computationally efficient but it also provides conceptual insight into the economic worth of existing units. A series of snapshot optimization decisions using this algorithm has been implemented to develop long-range generation expansion plans. Two case studies illustrating the snapshot procedure on sample power system data are described.

Physics-Guided Deep Neural Networks for Power Flow Analysis

Abstract: Solving power flow (PF) equations is the basis of power flow analysis, which is important in determining the best operation of existing systems, performing security analysis, etc. However, PF equations can be out-of-date or even unavailable due to system dynamics, and uncertainties, making traditional numerical approaches infeasible. To address these concerns, researchers have proposed data-driven approaches to solve the PF problem by learning the mapping rules from historical system operation data. Nevertheless, prior data-driven approaches suffer from poor performance, and generalizability, due to overly simplified assumptions of the PF problem or ignorance of physical laws governing power systems. In this paper, we propose a physics-guided neural network to solve the PF problem, with an auxiliary task to rebuild the PF model. By encoding different granularity of Kirchhoff's laws, and system topology into the rebuilt PF model, our neural-network based PF solver is regularized by the auxiliary task, and constrained by the physical laws. The simulation results show that our physics-guided neural network methods achieve better performance, and generalizability compared to existing unconstrained data-driven approaches. Furthermore, we demonstrate that the weight matrices of the proposed neural networks embody power system physics by showing their similarities with the bus admittance matrices.

A Decoupled Control Strategy of Modular Multilevel Matrix Converter for Fractional Frequency Transmission System

Abstract: Fractional frequency transmission system (FFTS), also known as low-frequency ac transmission system, is a promising solution to offshore wind power integration. The ac/ac converter is the most important equipment in FFTS. The modular multilevel matrix converter (M3C) is widely regarded as the next-generation ac/ac converter, but its complex control remains a problem. A novel control strategy is proposed featuring its decoupling algorithm in this paper. Different from previous research, the proposed current control regulates current components of different frequencies separately in star-figure subconverters under their synchronous rotating frames (SRFs), where the current is transformed to dq -axis dc signals for a better performance. A novel algorithm named “cross-SRF decoupling algorithm” is proposed to overcome the tight coupling between the circulating currents of two different frequencies. The effectiveness of the proposed control strategy has been verified by the simulation results obtained from a 110 kV, 400 MW M3C system implemented in MATLAB /Simulink.

Overview on definition and classification of power system stability

Abstract: The problem of defining and classifying power system stability has been addressed by several previous CIGRE and IEEE task force reports. These earlier efforts, however, do not completely reflect current industry needs, experiences and understanding. In particular, the definitions are not precise and the classifications do not encompass all practical instability scenarios. This report developed by a task force set up jointly by the CIGRE study committee 38 and the IEEE power system dynamic performance committee addresses the issue of stability definition and classification in power systems from a fundamental viewpoint and closely examines the practical ramifications. The report aims to define power system stability more precisely, provide a systematic basis for its classification, and discuss linkages to related issues such as power system reliability and security.

Integrated optimal power flow for electric power and heat in a MicroGrid

Abstract: Optimal power flow (OPF) programs are employed for optimising the operation of electric power networks whilst satisfying all network constraints. Their formulation is based on electric power flow equations and power system constraints, while other energy systems, such as gas and heat, are insufficiently represented. A formulation of an integrated OPF for power, and heat networks in a MicroGrid is described. Flow equations representing electric power, hot water, and heat systems are considered. The model is demonstrated on a simple network with different operational constraints.