An economic-environmental asset planning in electric distribution networks considering carbon emission trading and demand response

Research output: Contribution to journalArticle

Researchers

Research units

  • Universidade Estadual Paulista Júlio de Mesquita Filho

Abstract

Initiatives such as government programs and investment in low-carbon technologies have been adopted to mitigate the carbon emissions in the electricity sector. These initiatives have resulted in new challenges in the power sector, and to address them adequately, innovative frameworks are required in the electric distribution network (EDN) expansion planning and operation problems. Therefore, this work proposes an environmentally committed asset planning approach to remedy the existing issues to some extent. The proposed strategy investigates the benefits of the simultaneous allocation of several assets such as capacitor banks (CBs), distributed generation (DG) units based on renewable energy sources, and energy storage systems (ESSs). Moreover, an innovative carbon emission trading scheme is formulated in the planning stage to mitigate the CO2 emissions while a demand response program is applied to modify the consumption behavior. The proposed approach is formulated as a two-stage robust mixed-integer programming model, which considers uncertainties associated with the electricity demand and renewable-based DG. To cope with the difficulties of this complex model, utilizing an efficient decomposition algorithm, such as the C&CG decomposition algorithm, is essential. The potential of the proposed approach is studied under different operating conditions and via several test cases on a 137-node EDN. In addition, to validate the performance of the proposed carbon emission scheme, a multi-region 54-node distribution network is adequately evaluated. Results show that by considering simultaneously multiple planning alternatives, carbon emission trading scheme, and the demand response program, the total CO2 emissions are reduced by up to 15%.

Details

Original languageEnglish
Article number106202
Number of pages12
JournalElectric Power Systems Research
Volume181
Publication statusPublished - 1 Apr 2020
MoE publication typeA1 Journal article-refereed

    Research areas

  • Asset planning, Carbon emission trading, Demand response, Distributed generation, Distribution networks

ID: 40545341