Voltage Quality Assessment in a Distribution System With Distributed Generation—A Probabilistic Load Flow Approach

There has been growing concern in distribution system planning regarding the potential impacts of distributed generation (DG) on power quality, specifically with regards to voltage limits, voltage imbalance, and flicker. The intermittent nature of renewable energy resources, such as wind and solar, makes a deterministic approach infeasible. It has been shown in the literature that probabilistic approaches must be adopted to truly assess the impact of DG units on the power system. This paper presents the findings of a probabilistic load-flow-based approach regarding the effects of renewable energy resources on the voltage quality in a distribution system. Statistical models have been utilized for modeling load, wind speed, and solar irradiance. Due to the unique nature of analysis, short duration variations of renewable resources have been modeled and taken into account. Simulation results are provided indicating how voltage quality is affected by distributed generation, especially on feeders with voltage regulators.

[1]  J. Driesen,et al.  Distributed generation: challenges and possible solutions , 2006, 2006 IEEE Power Engineering Society General Meeting.

[2]  J.G. Vlachogiannis,et al.  Probabilistic Constrained Load Flow Considering Integration of Wind Power Generation and Electric Vehicles , 2009, IEEE Transactions on Power Systems.

[3]  S. Conti,et al.  Probabilistic Load Flow for Distribution Networks with Photovoltaic Generators Part 1: Theoretical Concepts and Models , 2007, 2007 International Conference on Clean Electrical Power.

[4]  Z. Hu,et al.  A probabilistic load flow method considering branch outages , 2006, IEEE Transactions on Power Systems.

[5]  L.A. Kojovic,et al.  Summary of Distributed Resources Impact on Power Delivery Systems , 2008, IEEE Transactions on Power Delivery.

[6]  Nikos D. Hatziargyriou,et al.  Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities , 2007 .

[7]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems , 2004 .

[8]  Stefan Kilyeni,et al.  Transmission Planning - a Probabilistic Load Flow Perspective , 2008 .

[9]  William Kersting,et al.  Distribution System Modeling and Analysis , 2001, Electric Power Generation, Transmission, and Distribution: The Electric Power Engineering Handbook.

[10]  Arindam Ghosh,et al.  Voltage imbalance analysis in residential low voltage distribution networks with rooftop PVs , 2011 .

[11]  B. Bak-Jensen,et al.  Probabilistic load flow: A review , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[12]  R. F. Simmons,et al.  Probabilistic power-flow techniques extended and applied to operational decision making , 1976 .

[13]  Chun-Lien Su,et al.  Stochastic Evaluation of Voltages in Distribution Networks With Distributed Generation Using Detailed Distribution Operation Models , 2010, IEEE Transactions on Power Systems.

[14]  Nikos D. Hatziargyriou,et al.  Probabilistic constrained load flow for optimizing generator reactive power resources , 2000 .

[15]  Ying-Yi Hong,et al.  Optimal VAR Control Considering Wind Farms Using Probabilistic Load-Flow and Gray-Based Genetic Algorithms , 2009, IEEE Transactions on Power Delivery.

[16]  L Y Pao,et al.  Control of Wind Turbines , 2011, IEEE Control Systems.

[17]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems: Masters/Electric Power Systems , 2004 .

[18]  Juan Jose Corrales Hernandez,et al.  Guidelines for the technical assessment of harmonic, flicker and unbalance emission limits for PV-di , 2011 .

[19]  Chun-Lien Su,et al.  DISTRIBUTION PROBABILISTIC LOAD FLOW SOLUTION CONSIDERING NETWORK RECONFIGURATION AND VOLTAGE CONTROL DEVICES , 2005 .

[20]  N.D. Hatziargyriou,et al.  Voltage control settings to increase wind power based on probabilistic load flow , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[21]  A. Feijoo,et al.  Probabilistic Load Flow Including Wind Power Generation , 2011, IEEE Transactions on Power Systems.