http://iet.metastore.ingenta.com
1887

DG planning incorporating demand flexibility to promote renewable integration

DG planning incorporating demand flexibility to promote renewable integration

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The integration of demand flexibility in distributed generation (DG) planning either lacks accuracy or ignores the potential of the behaviour of consumers in promoting the integration of renewables. This study proposes a DG planning model coordinating demand flexibility, in which the DG expansion plan and the behaviour of consumers in demand response (DR) programmes are co-optimised for the highest social welfare and the optimal utilisation of renewable generation. Consequently, the supply cost is reduced by utilising higher renewable generation instead of buying electricity from the grid. A share of the cost savings is allocated to the consumers to encourage their participation in DR programmes. Simulation results show that the expansion capacity of renewable generation is increased by 7.4% compared with no demand flexibility incorporation, and the social welfare is increased by up to 13.5% compared with no DG installation and 3.1% compared with no demand flexibility incorporation. Besides, the DR programmes carried out in the distribution system interact with the DG expansion plan, and higher subsidy rates in DR programmes could further promote the integration of renewables.

References

    1. 1)
      • 1. Labisa, P.E., Visandeb, R.G., Pallugnac, R.C., et al: ‘The contribution of renewable distributed generation in mitigating carbon dioxide emissions’, Renew. Sustain. Energy Rev., 2011, 15, (9), pp. 48914896.
    2. 2)
      • 2. Paliwal, P., Patidar, N.P., Nema, R.K.: ‘Planning of grid integrated distributed generators: a review of technology, objectives and techniques’, Renew. Sustain. Energy Rev., 2014, 40, pp. 557570.
    3. 3)
      • 3. Singh, B., Sharma, J.: ‘A review on distributed generation planning’, Renew. Sustain. Energy Rev., 2017, 76, pp. 529544.
    4. 4)
      • 4. Pesaran, H.A.M., Huy, P.D., Ramachandaramurthy, V.K.: ‘A review of the optimal allocation of distributed generation: objectives, constraints, methods, and algorithms’, Renew. Sustain. Energy Rev., 2017, 75, pp. 293312.
    5. 5)
      • 5. Liu, M., Quilumba, F.L., Lee, W.: ‘A collaborative design of aggregated residential appliances and renewable energy for demand response participation’, IEEE Trans. Ind. Appl., 2016, 51, (5), pp. 35613569.
    6. 6)
      • 6. Ali, M., Degefa, M.Z., Humayun, M., et al: ‘Increased utilization of wind generation by coordinating the demand response and real-time thermal rating’, IEEE Trans. Power Syst., 2016, 31, (5), pp. 37373746.
    7. 7)
      • 7. Yang, Q., Fang, X.: ‘Demand response under real-time pricing for domestic households with renewable DGs and storage’, IET Gener. Transm. Distrib., 2017, 11, (8), pp. 19101918.
    8. 8)
      • 8. Gottwalt, S., Gärttner, J., Schmeck, H., et al: ‘Modeling and valuation of residential demand flexibility for renewable energy integration’, IEEE Trans. Smart Grid, 2017, 8, (6), pp. 25652574.
    9. 9)
      • 9. Asensio, M., Meneses de Quevedo, P., Muñoz-Delgado, G., et al: ‘Joint distribution network and renewable energy expansion planning considering demand response and energy storage — part I: stochastic programming model’, IEEE Trans. Smart Grid, 2018, 9, (2), pp. 655666.
    10. 10)
      • 10. Asensio, M., Meneses de Quevedo, P., Muñoz-Delgado, G., et al: ‘Joint distribution network and renewable energy expansion planning considering demand response and energy storage — part II: numerical results’, IEEE Trans. Smart Grid, 2018, 9, (2), pp. 667675.
    11. 11)
      • 11. Calvillo, C.F., Sánchez-Miralles, A., Villar, J., et al: ‘Optimal planning and operation of aggregated distributed energy resources with market participation’, Appl. Energy, 2016, 182, pp. 340357.
    12. 12)
      • 12. Pina, A., Silva, C., Ferrão, P.: ‘The impact of demand side management strategies in the penetration of renewable electricity’, Energy, 2012, 41, (1), pp. 128137.
    13. 13)
      • 13. Humayd, A.S.B., Bhattacharya, K.: ‘Distribution system planning to accommodate distributed energy resources and PEVs’, Electr. Power Syst. Res., 2017, 145, pp. 111.
    14. 14)
      • 14. Erdinc, O., Paterakis, N.G., Pappi, I.N., et al: ‘A new perspective for sizing of distributed generation and energy storage for smart households under demand response’, Appl. Energy, 2015, 143, pp. 2637.
    15. 15)
      • 15. Moura, P.S., Almeida, A.T.: ‘Multi-objective optimization of a mixed renewable system with demand-side management’, Renew. Sustain. Energy Rev., 2010, 14, (5), pp. 14611468.
    16. 16)
      • 16. Fini, A.S., Moghaddam, M.P., Sheikh-El-Eslami, M.K.: ‘An investigation on the impacts of regulatory support schemes on distributed energy resource expansion planning’, Renew. Energy, 2013, 53, pp. 339349.
    17. 17)
      • 17. Wang, Z., Chen, Y., Mei, S., et al: ‘Optimal expansion planning of isolated microgrid with renewable energy resources and controllable loads’, IET Renew. Power Gener., 2017, 11, (7), pp. 931940.
    18. 18)
      • 18. Hejeejo, R., Qiu, J., Brinsmead, T.S., et al: ‘Sustainable energy system planning for the management of MGs: a case study in New South Wales, Australia’, IET Renew. Power Gener., 2017, 11, (2), pp. 228238.
    19. 19)
      • 19. Choi, D.G., Thomas, V.M.: ‘An electricity generation planning model incorporating demand response’, Energy. Policy, 2012, 42, pp. 429442.
    20. 20)
      • 20. Zeng, B., Zhang, J., Yang, X., et al: ‘Integrated planning for transition to low-carbon distribution system with renewable energy generation and demand response’, IEEE Trans. Power Syst., 2014, 29, (3), pp. 11531165.
    21. 21)
      • 21. Jin, S., Botterud, A., Ryan, S.M.: ‘Impact of demand response on thermal generation investment with high wind penetration’, IEEE Trans. Smart Grid, 2013, 4, (4), pp. 23742383.
    22. 22)
      • 22. Ma, K., Yao, T., Yang, J., et al: ‘Residential power scheduling for demand response in smart grid’, Int. J. Electr. Power Energy Syst., 2016, 78, pp. 320325.
    23. 23)
      • 23. Demand bidding program – PG&E’. Available at https://www.pge.com/includes/docs/pdfs/mybusiness/energysavingsrebates/demandresponse/dbp/fs_dbp.pdf, accessed 27 January 2018.
    24. 24)
      • 24. Dang, C., Wang, X., Wang, X., et al: ‘Electrical model and control method of heat pump water heaters for promoting renewable integration’. Proc. China Int. Conf. Electricity Distribution (CICED), Xi'an, China, August 2016, pp. 15.
    25. 25)
      • 25. Erdinç, O., Taşcıkaraoğlu, A., Paterakis, N.G., et al: ‘End-user comfort oriented day-ahead planning for responsive residential HVAC demand aggregation considering weather forecasts’, IEEE Trans. Smart Grid, 2017, 8, (1), pp. 272362.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2018.5648
Loading

Related content

content/journals/10.1049/iet-gtd.2018.5648
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address