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Market strategy options to implement Thailand demand response program policy

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  • Sonsaard, Parinya
  • Ketjoy, Nipon
  • Mensin, Yodthong

Abstract

DR (Demand Response) is an energy management strategy for reducing electricity usage during high-demand and unbalanced problem between demand and supply, which can lead to reduction in power system investment costs and CO2 emission. This technology is especially suitable for the initial state of the power system transformation and demonstrates a good attitude in sustainable development view. DR also has the potential to improve the flexibility of Thailand power system in order to promote the growth of renewable energy (RE). This study analysed a DR business option where LAs (Load Aggregators) are the key actors that collect and managed committed DR resources. Our study proposed the establishment of LA#1, as lead and first level LAs, wherein LA#1 consists of state utilities. For non-utilities interested in the DR business, they will be designated as LA#2, or level two LAs, responsible for DR resources left out by LA#1. The study included an assessment of the DR market size, and analyses of our proposed DR business solution. The SWOT analysis showed that the strengths and opportunities outweighed the weaknesses and threats for a business option where the state utilities are the lead LAs and the ones primary doing the DR business. The BMC assessment provided a comprehensive analysis confirming that our proposed LA business operation, wherein having an LA#1 consisting of state utilities, should be the preferential DR business operation option under the current power market structure. The financial analysis also supported this business option of state utilities being LA#1.

Suggested Citation

  • Sonsaard, Parinya & Ketjoy, Nipon & Mensin, Yodthong, 2023. "Market strategy options to implement Thailand demand response program policy," Energy Policy, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:enepol:v:173:y:2023:i:c:s0301421522006073
    DOI: 10.1016/j.enpol.2022.113388
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    References listed on IDEAS

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    2. Eduardo J. Salazar & Mauro Jurado & Mauricio E. Samper, 2023. "Reinforcement Learning-Based Pricing and Incentive Strategy for Demand Response in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.

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