4.5 Article

Virtual storage capacity using demand response management to overcome intermittency of solar PV generation

Journal

IET RENEWABLE POWER GENERATION
Volume 11, Issue 14, Pages 1741-1748

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-rpg.2017.0036

Keywords

photovoltaic power systems; solar power; demand side management; load regulation; power generation control; buildings (structures); virtual storage capacity; solar PV generation intermittency; solar photovoltaic systems; distribution network; priority-based demand response management; DRM; virtual energy storage; load control; air conditioning systems; refrigerators; forecasted solar PV generation; data-driven simulations; weather data; mathematical models; multistorey residential buildings; renewable energy

Funding

  1. Republic of Singapore's National Research Foundation
  2. School of Electrical and Electronics Engineering, Nanyang Technological University

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The integration of solar photovoltaic (PV) systems into the distribution network creates various stability and reliability issues associated with the intermittency of solar PV power generation. Energy storage is a vital component required for overcoming the intermittency of solar PV. This study presents a priority-based demand response management (DRM) for loads with large time constants to create virtual energy storage. The virtual energy storage thus created can be used for partial levelling of intermittent output from solar PVs. The proposed DRM algorithm involves controlling loads with large time constants such as air conditioning systems and refrigerators based on the forecasted solar PV generation. The proposed method is evaluated using data-driven simulations, weather data and mathematical models. The proposed algorithm is highly suitable for megacities that have high number of multi-storey residential buildings. Utilising the virtual storage capacity available from the appliances will reduce the investment as well as the operation cost of renewable energy such as solar PV. Analyses on impact on temperature, percentage of interruptions, cost savings and impact on energy storage sizing are also presented for evaluating the performance of the proposed algorithm.

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