scholarly journals A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 269
Author(s):  
Enrico Dalla Maria ◽  
Mattia Secchi ◽  
David Macii
Keyword(s):  
Stochastic Model ◽  
Power Flow ◽  
Distribution Systems ◽  
Control Strategies ◽  
Flow Analysis ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Operating Conditions ◽  
Time Varying ◽  
Top Down

The study of the behavior of smart distribution systems under increasingly dynamic operating conditions requires realistic and time-varying load profiles to run comprehensive and accurate simulations of power flow analysis, system state estimation and optimal control strategies. However, due to the limited availability of experimental data, synthetic load profiles with flexible duration and time resolution are often needed to this purpose. In this paper, a top-down stochastic model is proposed to generate an arbitrary amount of synthetic load profiles associated with different kinds of users exhibiting a common average daily pattern. The groups of users are identified through a preliminary Ward’s hierarchical clustering. For each cluster and each season of the year, a time-inhomogeneous Markov chain is built, and its parameters are estimated by using the available data. The states of the chain correspond to equiprobable intervals, which are then mapped to a time-varying power consumption range, depending on the statistical distribution of the load profiles at different times of the day. Such distributions are regarded as Gaussian Mixture Models (GMM). Compared with other top-down approaches reported in the scientific literature, the joint use of GMM models and time-inhomogeneous Markov chains is rather novel. Furthermore, it is flexible enough to be used in different contexts and with different temporal resolution, while keeping the number of states and the computational burden reasonable. The good agreement between synthetic and original load profiles in terms of both time series similarity and consistency of the respective probability density functions was validated by using three different data sets with different characteristics. In most cases, the median values of synthetic profiles’ mean and standard deviation differ from those of the original reference distributions by no more than ±10% both within a typical day of each season and within the population of a given cluster, although with some significant outliers.

scholarly journals Pressure Retarded Osmosis Power Units Modelling for Power Flow Analysis of Electric Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6649
Author(s):  
Mario Llamas-Rivas ◽  
Alejandro Pizano-Martínez ◽  
Claudio R. Fuerte-Esquivel ◽  
Luis R. Merchan-Villalba ◽  
José M. Lozano-García ◽  
...  
Keyword(s):  
Steady State ◽  
Power Flow ◽  
Distribution Systems ◽  
Flow Analysis ◽  
Distribution Networks ◽  
Operating Conditions ◽  
Electric Response ◽  
Pressure Retarded Osmosis ◽  
Power Flow Analysis ◽  
Electric Distribution

Pressure retarded osmosis (PRO) power units, which produce electrical energy from salinity gradient sources located at coastlines, are a technology still in the process of maturation; however, there is an expectation that this technology will need to be integrated into electrical distribution networks. Such integration will drive changes in the electric response of the distribution systems which may lead to harmful operating conditions. Power flow analysis is a tool used to reveal the steady-state operating condition of distribution systems and which could be extended to study and address the integration of PRO power units. To the best of the authors’ knowledge, such extension of power flow analysis has not yet been addressed in the literature. Accordingly, this paper comprehensively provides a model to evaluate the electric current and complex power produced by PRO power units. This model is directly embedded in the forward-backward sweep (FBS) method, extending the power flow analysis of electric distribution systems in this way so as to consider the integration of PRO power units. The resulting approach permits revealing of the steady-state operating response of distribution systems and the effects that may be driven by the integration of PRO power units, as corroborated through numerical results on a 14-node test distribution system.

scholarly journals Impedance Matching-Based Power Flow Analysis for UPQC in Three-Phase Four-Wire Systems

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2702
Author(s):  
Xiaojun Zhao ◽  
Xiuhui Chai ◽  
Xiaoqiang Guo ◽  
Ahmad Waseem ◽  
Xiaohuan Wang ◽  
...  
Keyword(s):  
Power Flow ◽  
Control Strategies ◽  
Impedance Matching ◽  
Flow Analysis ◽  
Point Of View ◽  
Impedance Model ◽  
Power Flow Analysis ◽  
Three Phase ◽  
System Node ◽  
Power Quality Conditioner

Different from the extant power flow analysis methods, this paper discusses the power flows for the unified power quality conditioner (UPQC) in three-phase four-wire systems from the point of view of impedance matching. To this end, combined with the designed control strategies, the establishing method of the UPQC impedance model is presented, and on this basis, the UPQC system can be equivalent to an adjustable impedance model. After that, a concept of impedance matching is introduced into this impedance model to study the operation principle for the UPQC system, i.e., how the system changes its operation states and power flow under the grid voltage variations through discussing the matching relationships among node impedances. In this way, the nodes of the series and parallel converter are matched into two sets of impedances in opposite directions, which mean that one converter operates in rectifier state to draw the energy and the other one operates in inverter state to transmit the energy. Consequently, no matter what grid voltages change, the system node impedances are dynamically matched to ensure that output equivalent impedances are always equal to load impedances, so as to realize impedance and power balances of the UPQC system. Finally, the correctness of the impedance matching-based power flow analysis is validated by the experimental results.

Power flow analysis of unbalanced multiphase radial distribution systems

1988 ◽  
Vol 14 (1) ◽  
pp. 23-33 ◽  
Author(s):  
R.P. Broadwater ◽  
A. Chandrasekaran ◽  
C.T. Huddleston ◽  
A.H. Khan
Keyword(s):  
Radial Distribution ◽  
Power Flow ◽  
Distribution Systems ◽  
Flow Analysis ◽  
Power Flow Analysis

scholarly journals Power Flow Analysis of Distribution Systems with Large-Scale Wind and Conventional Energy Generation

2013 ◽  
pp. 1117-1120
Author(s):  
A. Gopnzález ◽  
A. Madrazo ◽  
R. Robles ◽  
R. Domingo ◽  
M. Mañana ◽  
...  
Keyword(s):  
Power Flow ◽  
Distribution Systems ◽  
Large Scale ◽  
Flow Analysis ◽  
Energy Generation ◽  
Power Flow Analysis

scholarly journals Techno-Economic Models For Integration Of Wind Energy

2021 ◽  
Author(s):  
Chandrabhanu O.G. Kankanamalage
Keyword(s):  
Wind Energy ◽  
Electricity Markets ◽  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Flow Analysis ◽  
Power Flow Analysis ◽  
Wind Generators ◽  
Three Phase ◽  
Intelligent Models

This thesis focusses on three specific areas of integrating wind energy with power systems: 1) technical modeling of wind generators for power flow analysis, 2) probabilistic modeling of wind generators for planning studies, and 3) economic modeling for integration of wind energy in electricity markets. Wind generator output is a function of wind speed and 3-phase terminal voltages. Complete nonlinear three-phase models of wind generators are accurate but are computationally cumbersome and unsuitable for power flow analysis purposes. Intelligent models of wind generators are proposed for their accurate representation and use in power flow analysis algorithms. The main advantages of these intelligent models of wind generators are their mathematical simplicity, computational speed and numerical accuracy when the generators are connected to unbalanced three-phase distribution systems. These proposed intelligent models of wind generators were tested with the three-phase, unbalanced, IEEE 37-bus test system. The results show that the intelligent models of wind generators are computationally ten times faster than exact nonlinear models. In addition, simplicity of the proposed intelligent models of wind generators allows easy integration into commercial software such as PSS®E and PSS®SINCAL. In the second study, a probabilistic model of wind generators was integrated with algorithm for distribution system analysis. The proposed probabilistic power flow analysis method for distribution systems takes into account the stochastic nature of wind generation and forecasted bus-wise peak load. Probability distribution functions for bus voltages are reconstructed. The proposed method is tested on a modified 70-bus distribution system and the results are reported. Thirdly, an economic integration model for wind generators with electricity markets is proposed. The proposed model is in the form of a Wind Generators Cooperative (WGC). This proposed model overcomes challenges posed by uncertainty and intermittency of wind generation. The proposed cooperative model maximizes returns for wind generators by minimizing the effect of uncertainty by smoothing effect and using pumped-hydro facilities. A case study with actual data from Ontario (Canada) was completed. Analyses clearly demonstrate that the WGC increases returns to wind generators and reduces their exposure to uncertainty.

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