Have a personal or library account? Click to login

Optimal Energy Management in a Smart Micro Grid with Demand Side Participation

Environmental and Climate Technologies
Volume 26 (2022): Issue 1 (January 2022)
By:
Open Access
|May 2022

References

  1. [1] Odugbesan J. A., Rjoub H. Relationship among economic growth, energy consumption, CO2 emission, and urbanization: evidence from MINT countries. Sage Open 2020:10(2). https://doi.org/10.1177/215824402091464810.1177/2158244020914648
    Search in Google ScholarBack to article
  2. [2] Adebayo T. S., et al. Sustainability of energy-induced growth nexus in Brazil: do carbon emissions and urbanization matter? Sustainability 2021:13(8):4371. https://doi.org/10.3390/su1308437110.3390/su13084371
    Search in Google ScholarBack to article
  3. [3] Ahmed A. A. A. Corporate attributes and disclosure of accounting information: Evidence from the big five banks of China. Journal of Public Affairs 2021:21(3):2244. https://doi.org/10.1002/pa.224410.1002/pa.2244
    Search in Google ScholarBack to article
  4. [4] Adebayo T. S., Rjoub H. A new perspective into the impact of renewable and nonrenewable energy consumption on environmental degradation in Argentina: a time–frequency analysis. Environmental Science and Pollution Research 2022:29(11):16028–16044. https://doi.org/10.1007/s11356-021-16897-610.1007/s11356-021-16897-634637122
    Search in Google ScholarBack to article
  5. [5] Ahmed Z., et al. Economic growth, renewable energy consumption, and ecological footprint: exploring the role of environmental regulations and democracy in sustainable development. Sustainable Development 2021:1–11. https://doi.org/10.1002/sd.225110.1002/sd.2251
    Search in Google ScholarBack to article
  6. [6] Sibuea M. B., et al. The impact of renewable energy and economic development on environmental quality of ASEAN countries. AgBioForum 2021:23(1):12–21. https://hdl.handle.net/10355/86623
    Search in Google ScholarBack to article
  7. [7] Talha M., et al. Impact of Oil Prices, Energy Consumption and Economic Growth on the Inflation Rate in Malaysia. Cuadernos de Economía 2021:44(124):26–32.
    Search in Google ScholarBack to article
  8. [8] Athiyaman A., Magapa T. Market Intelligence from The Internet: An Illustration Using the Biomass Heating Industry. International Journal of Economics and Finance Studies 2019:11(1):1–6. https://doi.org/10.34109/ijefs.20191110110.34109/ijefs.201911101
    Search in Google ScholarBack to article
  9. [9] Ghaffari M., Javadian N., Tavakkoli-Moghaddam R. Controlling the bullwhip effect in a supply chain network with an inventory replenishment policy by a robust control method. Journal of Optimization in Industrial Engineering 2014:7(16):75–82.
    Search in Google ScholarBack to article
  10. [10] Ghaffari M., Javadian N., Tavakkoli-Moghaddam, R. Employing an Imperialist Competitive Algorithm to Minimize the Bullwhip Effect in a Supply Chain. World Applied Sciences Journal 2012:20(12):1629–1635.
    Search in Google ScholarBack to article
  11. [11] Zajmi L., Ahmed F. Y., Jaharadak A. A. Concepts, methods, and performances of particle swarm optimization, backpropagation, and neural networks. Applied Computational Intelligence and Soft Computing 2018:2018: 9547212. https://doi.org/10.1155/2018/954721210.1155/2018/9547212
    Search in Google ScholarBack to article
  12. [12] Omar H. A. M. B. B., Ali M., Jaharadak A. Green supply chain integrations and corporate sustainability. Uncertain Supply Chain Management 2019:7(4):713–726. http://doi.org/10.5267/j.uscm.2019.3.00110.5267/j.uscm.2019.3.001
    Search in Google ScholarBack to article
  13. [13] Paul S. C., Rosid M. H. O., Biswas J. Impact of Energy and Natural Resources Rent on FDI: An Analysis through POLS, DK, 2SLS and GMM Models. Energy Economics Letters 2021:8(2):122–133. https://doi.org/10.18488/journal.82.2021.82.122.13310.18488/journal.82.2021.82.122.133
    Search in Google ScholarBack to article
  14. [14] Singh K., Srivastava A. R&D Management as a Driver for Sustainable Agricultural Innovation and Adoption: Evidence from India. Proceedings of the IOP Conference Series: Earth and Environmental Science 2021:795:012009. https://doi.org/10.1088/1755-1315/795/1/01200910.1088/1755-1315/795/1/012009
    Search in Google ScholarBack to article
  15. [15] Singh K. V. Green publicizing to gratify buyer’s demands and sustainable growth: Challenges and forecasts. Materials Today: Proceedings 2021:37(P2):2807–2811. https://doi.org/10.1016/j.matpr.2020.08.65310.1016/j.matpr.2020.08.653
    Search in Google ScholarBack to article
  16. [16] Li M., et al. Renewable energy resources investment and green finance: Evidence from China. Resources Policy 2021:74:102402. https://doi.org/10.1016/j.resourpol.2021.10240210.1016/j.resourpol.2021.102402
    Search in Google ScholarBack to article
  17. [17] Oladipupo S. D., et al. Impact of Globalization and Renewable Energy Consumption on Environmental Degradation: A Lesson for South Africa. International Journal of Renewable Energy Development 2022:11(1):145–155. https://doi.org/10.14710/ijred.2022.4045210.14710/ijred.2022.40452
    Search in Google ScholarBack to article
  18. [18] Molajou A., et al. A new paradigm of water, food, and energy nexus. Environmental Science and Pollution Research 2021. https://doi.org/10.1007/s11356-021-13034-110.1007/s11356-021-13034-133634401
    Search in Google ScholarBack to article
  19. [19] Nourani V., et al. An integrated simulation-optimization framework to optimize the reservoir operation adapted to climate change scenarios. Journal of Hydrology 2020:587:125018. https://doi.org/10.1016/j.jhydrol.2020.12501810.1016/j.jhydrol.2020.125018
    Search in Google ScholarBack to article
  20. [20] Tarofder A. K., et al. Impact of ecological factors on nationwide supply chain performance. Ekoloji 2019:28(107):695–704.
    Search in Google ScholarBack to article
  21. [21] Irandoost A., Kargar S. An integrated optimization of routing and scheduling of liner ships in offshore logistics management. Journal of Research in Science, Engineering and Technology 2021:9(02):17–35.
    Search in Google ScholarBack to article
  22. [22] Mirsharafeddin S. A Bi-Objective Optimization of Portfolio Risk Response Strategies in Oil and Gas Projects. Journal of Research in Science, Engineering and Technology 2020:8(4):1–18. https://doi.org/10.24200/jrset.vol8iss4pp1-1810.24200/jrset.vol8iss4pp1-18
    Search in Google ScholarBack to article
  23. [23] Ahmadi Z., Haghighi M., Validi Z. (2020). A Novel Approach for Energy Optimization in Distributed Databases in Wireless Network Applications. Journal of Research in Science, Engineering and Technology 2020:8(2):7–11. https://doi.org/10.24200/jrset.vol8iss2pp7-1110.24200/jrset.vol8iss2pp7-11
    Search in Google ScholarBack to article
  24. [24] Zainal A. G., Yulianto H., Yanfika H. Financial benefits of the environmentally friendly aquaponic media system. Proceedings of the IOP Conference Series: Earth and Environmental Science 2021:739(1):012024. https://doi.org/10.1088/1755-1315/739/1/01202410.1088/1755-1315/739/1/012024
    Search in Google ScholarBack to article
  25. [25] Jermsittiparsert K. Linkage Between Energy Consumption, natural Environment Pollution, and Public Health Dynamics in ASEAN. International Journal of Economics and Finance Studies 2021:13(2):1–21.
    Search in Google ScholarBack to article
  26. [26] Hou R., et al. Assessing of impact climate parameters on the gap between hydropower supply and electricity demand by RCPs scenarios and optimized ANN by the improved Pathfinder (IPF) algorithm. Energy 2021:237:121621. https://doi.org/10.1016/j.energy.2021.12162110.1016/j.energy.2021.121621
    Search in Google ScholarBack to article
  27. [27] Zhu P., et al. Application of probability decision system and particle swarm optimization for improving soil moisture content. Water Supply 2021:21(8):4145–4152. https://doi.org/10.2166/ws.2021.16910.2166/ws.2021.169
    Search in Google ScholarBack to article
  28. [28] Trehub M., et al. Evaluating Simulation and Development of Algorithms of Energy Consumption Reduction Based on Wireless Sensor Networks. UCT Journal of Research in Science, Engineering and Technology 2019:7(3):18–24. https://doi.org/10.24200/jrset.vol7iss03pp18-2410.24200/jrset.vol7iss3pp18-24
    Search in Google ScholarBack to article
  29. [29] Zhang J., et al. Optimal model evaluation of the proton-exchange membrane fuel cells based on deep learning and modified African Vulture Optimization Algorithm. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2022:44:287–305. https://doi.org/10.1080/15567036.2022.204395610.1080/15567036.2022.2043956
    Search in Google ScholarBack to article
  30. [30] Waseel A. M., et al. Central heating by seasonal sensible heat storage of solar thermal energy. International Journal of Innovative Research and Scientific Studies 2021:4(2):100–11010.53894/ijirss.v4i2.63
    Search in Google ScholarBack to article
  31. [31] Ketut N., et al. Analysis of symbolic violence practices in balinese vernacular architecture: A case study in Bali, Indonesia. International Journal of Innovation, Creativity and Change 2020:13(5):184–194.
    Search in Google ScholarBack to article
  32. [32] Rahman N., et al. Impact of strategic leadership on organizational performance, strategic orientation and operational strategy. Management Science Letters 2018:8(12):1387–1398. http://doi.org/10.5267/j.msl.2018.9.00610.5267/j.msl.2018.9.006
    Search in Google ScholarBack to article
  33. [33] Chamandoust H., et al. Day-ahead scheduling problem of smart micro-grid with high penetration of wind energy and demand side management strategies. Sustainable Energy Technologies and Assessments 2020:40:100747. https://doi.org/10.1016/j.seta.2020.10074710.1016/j.seta.2020.100747
    Search in Google ScholarBack to article
  34. [34] Chamandoust H., et al. Optimal Hybrid System Design Based on Renewable Energy Resources. IEEE Smart Grid Conference (SGC) 2017. https://doi.org/10.1109/SGC.2017.830887810.1109/SGC.2017.8308878
    Search in Google ScholarBack to article
  35. [35] Chamandoust H., et al. Multi-objective performance of smart hybrid energy system with Multi-optimal participation of customers in day-ahead energy market. Energy and Buildings 2020:216:109964. https://doi.org/10.1016/j.enbuild.2020.10996410.1016/j.enbuild.2020.109964
    Search in Google ScholarBack to article
  36. [36] Chamandoust H., et al. Tri-objective optimal scheduling of smart energy hub system with schedulable loads. Journal of Cleaner Production 2019:236:117584. https://doi.org/10.1016/j.jclepro.2019.07.05910.1016/j.jclepro.2019.07.059
    Search in Google ScholarBack to article
  37. [37] Chamandoust H., et al. Scheduling of Smart Micro Grid Considering Reserve and Demand Side Management. IEEE Smart Grid Conference (SGC) 2018. https://doi.org/10.1109/SGC.2018.877792610.1109/SGC.2018.8777926
    Search in Google ScholarBack to article
  38. [38] Chamandoust H., et al. Multi-objective operation of smart stand-alone microgrid with the optimal performance of customers to improve economic and technical indices. Journal of Energy Storage 2020:31:101738. https://doi.org/10.1016/j.est.2020.10173810.1016/j.est.2020.101738
    Search in Google ScholarBack to article
  39. [39] Chamandoust H., et al. Energy management of a smart autonomous electrical grid with a hydrogen storage system. International journal of hydrogen energy 2021:46:17608–17626. https://doi.org/10.1016/j.ijhydene.2021.02.17410.1016/j.ijhydene.2021.02.174
    Search in Google ScholarBack to article
  40. [40] Chamandoust H. Optimal hybrid participation of customers in a smart micro-grid based on day-ahead electrical market. Artificial Intelligence Review 2022. https://doi.org/10.1007/s10462-022-10154-z10.1007/s10462-022-10154-z
    Search in Google ScholarBack to article
  41. [41] Chamandoust H., et al. Tri-objective scheduling of residential smart electrical distribution grids with optimal joint of responsive loads with renewable energy sources. Journal of Energy Storage 2019:27:101112. https://doi.org/10.1016/j.est.2019.10111210.1016/j.est.2019.101112
    Search in Google ScholarBack to article
  42. [42] Javadi M. S., et al. A Multi-Objective Model for Home Energy Management System Self-Scheduling using the Epsilon-Constraint Method. IEEE 2020. https://doi.org/10.1109/CPE-POWERENG48600.2020.916152610.1109/CPE-POWERENG48600.2020.9161526
    Search in Google ScholarBack to article
  43. [43] Javadi M. S., et al. Self-scheduling model for home energy management systems considering the end-users discomfort index within price-based demand response programs. Sustainable Cities and Society 2021:68:102792. https://doi.org/10.1016/j.scs.2021.10279210.1016/j.scs.2021.102792
    Search in Google ScholarBack to article
  44. [44] Ab Yajid M. S. Mediating Role of Organizational Culture on the Association between Business Social Responsibility and Organization Performance in Nigeria. Systematic Reviews in Pharmacy 2020:11(1):646–653.
    Search in Google ScholarBack to article
  45. [45] Pambreni Y., et al. The influence of total quality management toward organization performance. Management Science Letters 2019:9(9):1397–1406. http://doi.org/10.5267/j.msl.2019.5.01110.5267/j.msl.2019.5.011
    Search in Google ScholarBack to article
  46. [46] Adebayo S., et al. A Time-Varying Analysis between Financial Development and Carbon Emissions: Evidence from the MINT countries. Energy & Environment 2022.
    Search in Google ScholarBack to article
  47. [47] Adebayo S., et al. Asymmetric effect of structural change and renewable energy consumption on carbon emissions: designing an SDG framework for Turkey. Environment, Development and Sustainability 2022. https://doi.org/10.1007/s10668-021-02065-w10.1007/s10668-021-02065-w872390735002481
    Search in Google ScholarBack to article
  48. [48] Van Huong N., et al. Economic Impact of Climate Change on Agriculture: A Case of Vietnam. AgBioForum 2022:24(1):1–12.
    Search in Google ScholarBack to article
  49. [49] Vo P. H., Ngo T. Q. The Role of Agricultural Financing and Development on Sustainability: Evidence from ASEAN Countries. AgBioForum 2021:23(1):22–31.
    Search in Google ScholarBack to article
  50. [50] Sadeghifam A. N., et al. Analysis of Windows Element for Energy Saving in a Tropical Residential Buildings in Order to Reduce the Negative Environmental Impacts. Journal of Environmental Treatment Techniques 2021:9(1):1–6. https://doi.org/10.47277/JETT/9(1)610.47277/JETT/9(1)6
    Search in Google ScholarBack to article
  51. [51] Dabachi U. M., et al. Energy consumption, energy price, energy intensity environmental degradation, and economic growth nexus in African OPEC countries: evidence from simultaneous equations models. Journal of Environmental Treatment Techniques 2020:8(1):403–409.
    Search in Google ScholarBack to article
  52. [52] Dwijendra N. K. A., et al. Modeling Social Impacts of High-Rise Residential Buildings during the Post-Occupancy Phase Using DEMATEL Method: A Case Study. Buildings 2021:11(11):504. https://doi.org/10.3390/buildings1111050410.3390/buildings11110504
    Search in Google ScholarBack to article
DOI: https://doi.org/10.2478/rtuect-2022-0018 | Journal eISSN: 2255-8837 | Journal ISSN: 1691-5208
Journal RSS Feed
Language: English
Page range: 228 - 239
Published on: May 12, 2022
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year
Keywords:
Energy management,
max-min fuzzy procedure,
multi-criteria optimization,
optimal participation of demand side,
weight sum method (WSM)
Related subjects:
Life sciences,
Life sciences, other

© 2022 Cheng-Jui Tseng, Ngakan Ketut Acwin Dwijendra, Maria Jade Catalan Opulencia, Sarvinoz Ganieva, Iskandar Muda, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

Previous articleVolume 26 (2022): Issue 1 (January 2022)Next article