Open Access
E3S Web Conf.
Volume 209, 2020
ENERGY-21 – Sustainable Development & Smart Management
Article Number 06022
Number of page(s) 9
Section Session 5. Reliability of Fuel and Energy Supply to the Consumer, Energy Security
Published online 23 November 2020
  1. REN21, “Renewables 2019 Global Status Report GSR”, (2019). [Google Scholar]
  2. Hurlbut, D. and Getman, D, “Greening the Grid: Implementing Renewable Energy Zones for Integrated Transmission and Generation Planning.” Webinar, (2015). [Google Scholar]
  3. Asian Renewable Energy Hub, “New proposal would provide renewable energy and manufacturing boost to Indonesia; Australia’s wind and solar resources to generate renewable energy”, (2018). [Google Scholar]
  4. [Google Scholar]
  5. [Google Scholar]
  6. Nguyen Thai Son, “Increasing the proportion of renewable energy sources in Vietnam’s Electricity Development Planning”, in Proceeding of International Scientific Conference “Model to Develop Ninh Thuan Province into The National Renewable Energy Center, Solutions and Criteria”, Ninh Thuan province, (2019). [Google Scholar]
  7. [Google Scholar]
  8. Prime Minister, “National Power Development Master Plan (PDP VII) for the 2011-2020 period, with a vision for 2030”, (2016). [Google Scholar]
  9. [Google Scholar]
  10. Minh Ha-Duong, Sven Teske, Dimitri Pescia, Mentari Pujantoro, “Options for wind power in Vietnam by 2030”, (2020). [Google Scholar]
  11. Vietnamese Deputy Prime Minister, Decision 13/2020/QD-TTg on Mechanisms to Promote the Development of Solar Power Projects in Viet Nam, (2020). [Google Scholar]
  12. Vietnamese Prime Minister, Decision No 39/2018/QĐ-TTg for adjusting and supplementing a number of articles of the Decision No 37/2011/QĐ-TTg on the mechanism to support the development of wind power projects in Vietnam, (2018). [Google Scholar]
  13. Planning of solar power development in Ninh Thuan, (2017). [Google Scholar]
  14. Planning of wind power development in Ninh Thuan in the period 2011-2020, vision to 2030, (2013). [Google Scholar]
  15. Joost Sissingh, Eric Arends (Wind Minds), Wind Energy Potential Vietnam, (2018). [Google Scholar]
  16. Vu Minh Phap, Nguyen Thuy Nga, “Feasibility Study of Rooftop Photovoltaic Power System For A Research Institute Towards Green Building In Vietnam”. EAI Endorsed Transactions on Energy Web, pp. 1-9, (2020). [Google Scholar]
  17. Vu Minh Phap, Le Thi Thuy Hang. “Comparison of Central Inverter and String Inverter for Solar Power Plant: Case Study in Vietnam”. Journal of Nuclear Engineering & Technology. 9(3):11–23p, (2019). [Google Scholar]
  18. Giap LUONG Ngoc, Maeda Takao, Vu Minh Phap, Nguyen Binh Khanh, Hồ Thị Bích Ngọc and B. T. Trung. “Comparative Study Of Velocity Deficit Calculation Methods For A Wind Farm In Vietnam.” IOSR Journal of Engineering, Vol 7 (9), (2017). [Google Scholar]
  19. Babatunde O M, Munda J L and Hamam Y 2019 A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage Int. J. of Energy Res 1-30 [Google Scholar]
  20. Das P, Mathur J, Bhakar R and Kanudia A 2018 Implications of short-term renewable energy resource intermittency in long-term power system planning Energy strategy reviews 22 1-15 [CrossRef] [Google Scholar]
  21. Sadeghi H, Rashidinejad M and Abdollahi A 2017 A comprehensive sequential review study through the generation expansion planning Renewable and Sustainable Energy Reviews 67 1369-1394 [CrossRef] [Google Scholar]
  22. Koltsaklis N E and Dagoumas A S 2018 State-of-the-art generation expansion planning: A review Applied energy 230 563-589 [CrossRef] [Google Scholar]
  23. Bylling H C, Pineda S and Boomsma T K 2018 The impact of short-term variability and uncertainty on long-term power planning Annals of Operations Research 1-25 [Google Scholar]
  24. Jones L E 2017 Renewable energy integration: practical management of variability uncertainty and flexibility in power grids Academic Press [Google Scholar]
  25. Oree V Hassen S Z S and Fleming P J 2017 Generation expansion planning optimisation with renewable energy integration: A review Renewable and Sustainable Energy Reviews 69 790-803 [CrossRef] [Google Scholar]
  26. Senatla M and Bansal R C 2018 Review of planning methodologies used for determination of optimal generation capacity mix: the cases of high shares of PV and wind IET Renewable Power Generation 12(11) 1222-1233 [CrossRef] [Google Scholar]
  27. Welsch M, Howells M, Hesamzadeh M R Ó, Gallachóir B et. al 2015 Supporting security and adequacy in future energy systems: The need to enhance long-term energy system models to better treat issues related to variability International Journal of Energy Research 39(3) 377-396 [Google Scholar]
  28. Poncelet K, Delarue E, Duerinck J, Six D and D’haeseleer W 2014 The importance of integrating the variability of renewables in long-term energy planning models In BAEE Research [Google Scholar]
  29. Després J, Hadjsaid N, Criqui P and Noirot I 2015 Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools Energy 80 486-495 [CrossRef] [Google Scholar]
  30. Bessa R, Moreira C, Silva B and Matos M 2014 Handling renewable energy variability and uncertainty in power systems operation Wiley Interdisciplinary Reviews: Energy and Environment 3(2) 156-178 [CrossRef] [Google Scholar]
  31. Vithayasrichareon P, Riesz J and MacGill I 2017 Operational flexibility of future generation portfolios with high renewables Applied energy 206 32-41 [Google Scholar]
  32. Moreira A, Pozo D, Street A and Sauma E 2017 Reliable renewable generation and transmission expansion planning: Co-optimizing system’s resources for meeting renewable targets IEEE Trans Power Syst 32(4) 3246-3257 [Google Scholar]
  33. Akinbulire T O, Oluseyi P O and Babatunde O M 2014 Techno-economic and environmental evaluation of demand side management techniques for rural electrification in ibadan nigeria Int J Energy Environ Eng 5(4) 375-385 [CrossRef] [Google Scholar]
  34. Denholm P and Hand M 2011 Grid flexibility and storage required to achieve very high penetration of variable renewable electricity Energy Policy 39(3) 1817-1830 [Google Scholar]
  35. Castillo A and Gayme D F 2014 Grid-scale energy storage applications in renewable energy integration: A survey Energy Conversion and Management 87 885-894 [Google Scholar]
  36. Ding J and Somani A 2010 April A long-term investment planning model for mixed energy infrastructure integrated with renewable energy In 2010 IEEE Green Technologies Conference pp 1-10 [Google Scholar]
  37. Li S, Coit D W and Felder F 2016 Stochastic optimization for electric power generation expansion planning with discrete climate change scenarios Electric Power Syst Res 140 401-412 [CrossRef] [Google Scholar]
  38. Farghal S A and Aziz M A 1988 Generation expansion planning including the renewable energy sources IEEE Transactions on Power Systems 3(3) 816-822 [CrossRef] [Google Scholar]
  39. Hu Z, Jewell W T 2013 Optimal generation expansion planning with integration of variable renewables and bulk energy storage systems In: 2013 1st IEEE Conference on Technologies for Sustainability (SusTech) pp 1-8 [Google Scholar]
  40. Aghaei J, Akbari M, Roosta A, Gitizadeh M and Niknam T 2012 Integrated renewable–conventional generation expansion planning using multiobjective framework IET Gener Transm Distrib 6(8) 773-784 [CrossRef] [Google Scholar]
  41. Pina A, Silva C A and Ferrão P 2013 High-resolution modeling framework for planning electricity systems with high penetration of renewables Applied Energy 112 215-223 [Google Scholar]
  42. Conejo A J, Carrion M and Morales J M 2010 Decision Making Under Uncertainty in Electricity Markets Springer [CrossRef] [Google Scholar]
  43. Powell W 2014 Energy and Uncertainty: Models and Algorithms for Complex Energy Systems AI Magazine 35(3) 8-21 [Google Scholar]
  44. Powell W B 2019 A unified framework for stochastic optimization European Journal of Operational Research 275(3) 795-821 [Google Scholar]
  45. Soroudi A and Amraee T 2013 Decision making under uncertainty in energy systems: State of the art Renewable and Sustainable Energy Reviews 28 376-384 [Google Scholar]
  46. Powell W B and Meisel S 2015 Tutorial on stochastic optimization in energy - Part I: Modeling and policies IEEE Transactions on Power Systems 31(2) 1459-1467 [CrossRef] [Google Scholar]
  47. Khazaei J and Powell W B 2015 SMART-Invest: a stochastic dynamic planning for optimizing investments in wind solar and storage in the presence of fossil fuels. The case of the PJM electricity market Energy Systems 1-27 [Google Scholar]
  48. Meisel S and Powell W B 2017 Dynamic decision making in energy systems with storage and renewable energy sources In Advances Energy System Optimization 87-101 [CrossRef] [Google Scholar]
  49. Meza J L C, Yildirim M B and Masud A S 2007 A model for the multiperiod multiobjective power generation expansion problem IEEE Trans Power Syst 22(2) 871-878 [Google Scholar]
  50. Tekiner H, Coit D W and Felder F 2010 A Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation Electr. Pow. Syst. Res. 80(12) 1394-1405 [CrossRef] [Google Scholar]
  51. Kies A, Schyska B, Viet D T, Heinemann L B D and Schramm S 2017 Large-Scale Integration of Renewable Power Sources into the Vietnamese Power System Energy Procedia 125 207–213 [Google Scholar]
  52. Noorollahi E, Fadai D, Ghodsipour S H and Shirazi M A 2017 Developing a new optimization framework for power generation expansion planning with the inclusion of renewable energy - A case study of Iran J. Renew Sustain Energy 9(1) [Google Scholar]
  53. Marchenko, M.A., Mikhailov, G.A. Distributed computing by the Monte Carlo method. Autom Remote Control 68, 888–900 (2007). [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.