A review of hosting capacity quantification methods for photovoltaics in low-voltage distribution grids

Haque, 2016, A review of high PV penetrations in LV distribution networks: Present status, impacts and mitigation measures, Renew Sustain Energy Rev, 62, 1195, 10.1016/j.rser.2016.04.025

Comello, 2018, The road ahead for solar PV power, Renew Sustain Energy Rev, 92, 744, 10.1016/j.rser.2018.04.098

Stetz T, Kraiczy M, Diwold K, Braun M, Bletterie B, Mayr C, et al. High Penetration PV in Local Distribution Grids Outcomes of the IEA PVPS Task 14 Subtask 2. In: 29th European Photovoltaic Solar Energy Conference and Exhibition, Amsterdam, Netherlands, 2014, p. 2176–83.

Bourgain G. Integrating Distributed Energy Resources in Today’s Electrical Energy System; Book Presenting the Results of the EU-DEEP Project; ExpandDER: Saint Denis le Plaine, France; 2009.

Even A. Integration of DER, presented at the EU-DEEP Workshop, 23-26 March 2004.

Bollen MHJ, Häger M. Power quality: interactions between distributed energy resources, the grid, and other customers, presented at the Renewable Energy-DER Workshop, December-2004.

Oliveira, 2018, PV hosting capacity dependence on harmonic voltage distortion in low-voltage grids: model validation with experimental data, Energies, 11, 465, 10.3390/en11020465

Shayani, 2011, Photovoltaic generation penetration limits in radial distribution systems, IEEE Trans Power Syst, 26, 1625, 10.1109/TPWRS.2010.2077656

Luthander, 2017, Large-scale integration of photovoltaic power in a distribution grid using power curtailment and energy storage, Sol Energy, 155, 1319, 10.1016/j.solener.2017.07.083

Smith JW, Dugan R, Sunderman W. Distribution modeling and analysis of high penetration PV. In: IEEE Power and Energy Society General Meeting, 2011, p. 1–7.

Smith JW, Dugan R, Rylander M, Key T. Advanced distribution planning tools for high penetration PV deployment. In: IEEE Power and Energy Society General Meeting, 2012, p. 1–7.

Heilscher G, Ebe F, Idlbi B, Morris J, Meier F. Evaluation of PV Hosting Capacities of Distribution Grids with Utilization of Solar-Roof-Potential-Analyses. In: International Conference on Electricity Distribution, Glasgow, 2017, p. 12–15.

Quiroz J, Reno M. Detailed grid integration analysis of distributed PV. In: 38th IEEE Photovoltaic Specialists Conference, 2012, p. 000596–601.

Baut JL, Zehetbauer P, Kadam S, Bletterie B, Hatziargyriou N, Smith J, et al. Probabilistic evaluation of the hosting capacity in distribution networks. In: IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2016, p. 1–6.

EPRI, Stochastic Analysis to Determine Feeder Hosting Capacity for Distributed Solar PV. EPRI-Electric Power Research Institute, Palo Alto, CA, Technical Report; 2012.

Key, 2015, New tools and methods work to integrate solar on local circuits, EPRI J, 1, 4

Georgilakis, 2013, Optimal distributed generation placement in power distribution networks: models, methods, and future research, IEEE Trans Power Syst, 28, 3420, 10.1109/TPWRS.2012.2237043

Nikmehr, 2015, Solving probabilistic load flow in smart distribution grids using heuristic methods, J Renew Sustain Energy, 7

Elsaiah, 2014, Analytical approach for placement and sizing of distributed generation on distribution systems, IET Gener Transm Distrib, 8, 1039, 10.1049/iet-gtd.2013.0803

Ebe F, Idlbi B, Morris J, Heilscher G, Meier F. Evaluation of PV hosting capacity of distribuion grids considering a solar roof potential analysis-Comparison of different algorithms. In: IEEE Manchester PowerTech, 2017, p. 1–6.

Bertini D, Moneta D, Merlo M, Falabretti D, Silvestri A, Silva De Assis Carneiro J. Hosting capacity of Italian LV distribution networks, presented at the 21st International Conference on Electricity Distribution, Frankfurt; 2011.

Kabir, 2016, Probabilistic load flow for distribution systems with uncertain PV generation, Appl Energy, 163, 343, 10.1016/j.apenergy.2015.11.003

Conti, 2007, Probabilistic load flow for distribution networks with photovoltaic generators part 1: theoretical concepts and models, 132

Tonkoski, 2012, Impact of high PV penetration on voltage profiles in residential neighborhoods, IEEE Trans Sustain Energy, 3, 518, 10.1109/TSTE.2012.2191425

Ismael, 2018, State-of-the-art of hosting capacity in modern power systems with distributed generation, Renew Energy, 130, 1002, 10.1016/j.renene.2018.07.008

Smith J. Stochastic Analysis to Determine Feeder Hosting Capacity for Distributed Solar PV. Electric Power Research Institute (EPRI), Knoxville, TN, USA, Technical update report; 2012.

Chaudhary, 2018, Voltage regulation mitigation techniques in distribution system with high PV penetration: A review, Renew Sustain Energy Rev, 82, 3279, 10.1016/j.rser.2017.10.017

Zubo, 2017, Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review, Renew Sustain Energy Rev, 72, 1177, 10.1016/j.rser.2016.10.036

Karimi, 2016, Photovoltaic penetration issues and impacts in distribution network – A review, Renew Sustain Energy Rev, 53, 594, 10.1016/j.rser.2015.08.042

Shivashankar, 2016, Mitigating methods of power fluctuation of photovoltaic (PV) sources – A review, Renew Sustain Energy Rev, 59, 1170, 10.1016/j.rser.2016.01.059

Eltawil, 2010, Grid-connected photovoltaic power systems: Technical and potential problems—A review, Renew Sustain Energy Rev, 14, 112, 10.1016/j.rser.2009.07.015

Adefarati, 2016, Integration of renewable distributed generators into the distribution system: a review, IET Renew Power Gener, 10, 873, 10.1049/iet-rpg.2015.0378

Obi, 2016, Trends and challenges of grid-connected photovoltaic systems – A review, Renew Sustain Energy Rev, 58, 1082, 10.1016/j.rser.2015.12.289

Rezaee Jordehi, 2016, Allocation of distributed generation units in electric power systems: A review, Renew Sustain Energy Rev, 56, 893, 10.1016/j.rser.2015.11.086

Ha, 2017, A review of the optimal allocation of distributed generation: objectives, constraints, methods, and algorithms, Renew Sustain Energy Rev, 75, 293, 10.1016/j.rser.2016.10.071

Aien, 2016, A comprehensive review on uncertainty modeling techniques in power system studies, Renew Sustain Energy Rev, 57, 1077, 10.1016/j.rser.2015.12.070

Aien, 2014, On possibilistic and probabilistic uncertainty assessment of power flow problem: A review and a new approach, Renew Sustain Energy Rev, 37, 883, 10.1016/j.rser.2014.05.063

Bollen, 2011

Fan, 2017, A method to determine the maximum generation capacity of distribution generation in low voltage distribution feeders, J Eng, 2017, 944, 10.1049/joe.2017.0470

Conti, 2007, Probabilistic load flow using Monte Carlo techniques for distribution networks with photovoltaic generators, Sol Energy, 81, 1473, 10.1016/j.solener.2007.02.007

Breker, 2015, Capacity of low-voltage grids for distributed generation: classification by means of stochastic simulations, IEEE Trans Power Syst, 30, 689, 10.1109/TPWRS.2014.2332361

Borkowska, 1974, Probabilistic load flow, IEEE Trans Power Appar Syst, PAS-93, 752, 10.1109/TPAS.1974.293973

Allan, 1977, Probabilistic techniques in a.c. load-flow analysis, Proc Inst Electr Eng UK, 124, 154, 10.1049/piee.1977.0027

Allan, 1981, Evaluation methods and accuracy in probabilistic load flow solutions, IEEE Trans Power Appar Syst, 100, 2539, 10.1109/TPAS.1981.316721

Emmanuel, 2017, The impact of single-phase grid-connected distributed photovoltaic systems on the distribution network using P-Q and P-V models, Int J Electr Power Energy Syst, 91, 20, 10.1016/j.ijepes.2017.03.001

Chen, 2010

Saadat, 2010

Heslop, 2014, Method for determining a PV generation limit on low voltage feeders for evenly distributed PV and Load, ISES Solar World Congress, 57, 207

Thomas MS, Ranjan R, Malik N. Deterministic load flow algorithm for balanced radial AC distribution systems. In: IEEE 5th Power India Conference, 2012, p. 1–6.

Ampofo DO, Otchere IK, Frimpong EA. An investigative study on penetration limits of distributed generation on distribution networks. In: IEEE PES Power Africa, 2017, p. 573–6.

Schwaegerl, 2005, Voltage control in distribution systems as a limitation of the hosting capacity for distributed energy resources, 1

Alam, 2013, Mitigation of rooftop solar pv impacts and evening peak support by managing available capacity of distributed energy storage systems, IEEE Trans Power Syst, 28, 3874, 10.1109/TPWRS.2013.2259269

Omran, 2010

Balamurugan, 2012, Impact of distributed generation on power distribution systems, Energy Procedia, 25, 93, 10.1016/j.egypro.2012.07.013

Parihar SS, Malik N. Power flow analysis of balanced radial distribution system with composite load model. In: Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2017, p. 160–5.

Heslop, 2016, Maximum PV generation estimation method for residential low voltage feeders, Sustain Energy Grids Netw, 7, 58, 10.1016/j.segan.2016.06.003

Deng, 2017, Harmonic Analysis of LV distribution networks with high PV penetration, 1

Hu, 2015, Potential harmonic resonance impacts of PV inverter filters on distribution systems, IEEE Trans Sustain Energy, 6, 151, 10.1109/TSTE.2014.2352931

Carollo R, Chaudhary SK, Pillai JR. Hosting capacity of solar photovoltaics in distribution grids under different pricing schemes. In: IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2015, p. 1–5.

Smith J, Rogers L, Rylander M. Integration of Hosting Capacity Analysis into Distribution Planning Tools. In: Electric Power Research Institute (EPRI), Palo Alto, California,USA, Technical Report; 2016.

Schwanz, 2017, Stochastic assessment of voltage unbalance due to single-phase-connected solar power, IEEE Trans Power Deliv, 32, 852, 10.1109/TPWRD.2016.2579680

Hoke, 2013, Steady-state analysis of maximum photovoltaic penetration levels on typical distribution feeders, IEEE Trans Sustain Energy, 4, 350, 10.1109/TSTE.2012.2225115

Mulenga, 2018, Impact of service and feeder cable upgrade on hosting capacity for single phase connected photovoltaics, 1

Bollen, 2017, Hosting capacity of the power grid for renewable electricity production and new large consumption equipment, Energies, 10, 1325, 10.3390/en10091325

Samet, 2018, Analytic time series load flow, Renew Sustain Energy Rev, 82, 3886, 10.1016/j.rser.2017.10.084

Xue Y, Sharma I, Kuruganti T, Nutaro J, Dong J, Olama M, et al. Voltage impact analyses of solar photovoltaics on distribution load tap changer operations. In: 2017 North American Power Symposium (NAPS), 2017, p. 1–6.

Marah B, Ekwue AO. Probabilistic load flows. In: 50th International Universities Power Engineering Conference (UPEC), 2015, p. 1–6.

Wan C, Xu Z, Dong ZY, Wong KP. Probabilistic load flow computation using first-order second-moment method. In: IEEE Power and Energy Society General Meeting, 2012, p. 1–6.

Zhao, 2017

Deboever, 2018, Fast Quasi-Static Time-Series (QSTS) for yearlong PV impact studies using vector quantization, Sol Energy, 159, 538, 10.1016/j.solener.2017.11.013

Behravesh, 2018, Stochastic analysis of solar and wind hybrid rooftop generation systems and their impact on voltage behavior in low voltage distribution systems, Sol Energy, 166, 317, 10.1016/j.solener.2018.03.063

Busatto, 2019, Including uncertainties from customer connections in calculating low-voltage harmonic impedance, IEEE Trans Power Deliv, 34, 606, 10.1109/TPWRD.2018.2881222

Zhouyang R, Wei Y, Xia Z, Yiming L, Yuan Y. Probabilistic power flow for distribution networks with photovoltaic generators. In: IEEE Power & Energy Society General Meeting, 2013, p. 1–5.

Constante-Flores GE, Illindala GE. Data-driven probabilistic power flow analysis for a distribution system with Renewable Energy sources using Monte Carlo Simulation. In: IEEE/IAS 53rd Industrial and Commercial Power Systems Technical Conference (I & CPS), 2017, p. 1–8.

Qureshi, 2019, A fast scalable quasi-static time series analysis method for PV impact studies using linear sensitivity model, IEEE Trans Sustain Energy, 10, 301, 10.1109/TSTE.2018.2833748

Rossi, 2015, Hosting capacity of distribution networks: evaluation of the network congestion risk due to distributed generation, 716

Rossi, 2017, Stochastic evaluation of distribution network hosting capacity: Evaluation of the benefits introduced by smart grid technology, 1

Kolenc, 2015, Assessment of maximum distributed generation penetration levels in low voltage networks using a probabilistic approach, Int J Electr Power Energy Syst, 64, 505, 10.1016/j.ijepes.2014.07.063

Navarro-Espinosa, 2016, Probabilistic impact assessment of low carbon technologies in LV distribution systems, IEEE Trans Power Syst, 31, 2192, 10.1109/TPWRS.2015.2448663

Killinger, 2018, On the search for representative characteristics of PV systems: data collection and analysis of PV system azimuth, tilt, capacity, yield and shading, Sol Energy, 173, 1087, 10.1016/j.solener.2018.08.051

Dong, 2010

Le DD, Pham KV, Ngo DV, Huynh KV, Nguyen NTA, Berizzi A. An enhancement to cumulant-based probabilistic power flow methodologies. In: IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA), 2015, p. 1–5.

Aien, 2012, Probabilistic load flow in correlated uncertain environment using unscented transformation, IEEE Trans Power Syst, 27, 2233, 10.1109/TPWRS.2012.2191804

Safitri, 2015, Monte Carlo-based stochastic analysis results for coordination of single-phase rooftop PVs in low voltage residential networks, Intell Indus Syst, 1, 359, 10.1007/s40903-015-0029-2

Begovic, 2016, Impact of stochastically distributed renewable PV generation on distribution network, 1

Broderick, 2013

Supponen A, Repo S. Impact evaluation of PV generation on LV networks. In: 2014 Power Systems Computation Conference, 2014, p. 1–7.

Torquato, 2018, A comprehensive assessment of PV hosting capacity on low-voltage distribution systems, IEEE Trans Power Deliv, 33, 1002, 10.1109/TPWRD.2018.2798707

Ding, 2017, On distributed PV hosting capacity estimation, sensitivity study, and improvement, IEEE Trans Sustain Energy, 8, 1010, 10.1109/TSTE.2016.2640239

Quiroz JE, Reno MJ, Broderick RJ. Time series simulation of voltage regulation device control modes. In: IEEE 39th Photovoltaic Specialists Conference (PVSC), 2013, p. 1700–5.

Reno MJ, Deboever J, Mather B. Motivation and requirements for quasi-static time series (QSTS) for distribution system analysis. In: IEEE Power & Energy Society General Meeting, 2017, p. 1–5.

Pagnetti, 2015, A simple and efficient method for fast analysis of renewable generation connection to active distribution networks, Electr Power Syst Res, 125, 133, 10.1016/j.epsr.2015.03.025

Silverman, 2014

Khoshkbar-Sadigh A, Smedley KM. The necessity of time-series simulation for investigation of large-scale solar energy penetration. In: IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2015, p. 1–5.

Beck, 2016, Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems, Appl Energy, 173, 331, 10.1016/j.apenergy.2016.04.050

Luthander, 2018

Fan, 2016, Evaluation of impact of integrated distributed generation on distribution network based on time-series analysis, 1

Joshi KA, Pindoriya NM. Reactive resource reallocation in DG integrated secondary distribution networks with time-series distribution power flow. In: 2014 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), 2014, p. 1–6.

Mather BA. Quasi-static time-series test feeder for PV integration analysis on distribution systems. In: IEEE Power and Energy Society General Meeting, 2012, p. 1–8.

Wang, 2018, Load aggregation methods for quasi-static power flow analysis on high PV penetration feeders, 1

Swedish Meteorological and Hydrological Institute (SMHI). (2015). STRÅNG – A Mesoscale Model for Solar Radiation. Available: http://strang.smhi.se/.