Online carbon footprint Allocation- a joint Price- and carbon Footprint: responsive demands model to reduce the GHG emissions and manage the electricity demand

• Grant number: 16/14319-7
• Support type: Scholarships abroad - Research Internship - Post-doctor
• Effective date (Start): October 15, 2016
• Effective date (End): October 14, 2017
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal researcher: José Roberto Sanches Mantovani
• Grantee: Mahdi Pourakbari Kasmaei
• Supervisor abroad: Javier Contreras Sanz
• Home Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
• Research place: Universidad de Castilla-La Mancha, Ciudad Real (UCLM), Spain
• Associated to the scholarship: 14/22828-3 - A mixed-integer nonlinear programming paradigm to solve multi fuel-based environmentally-constrained active-reactive optimal power flow, BP.PD

Abstract

This research project is conducted as a part of the Postdoctoral Research, funded by (Fundação de Amparo à Pesquisa do Estado de São Paulo) FAPESP, No. 2014/22828-3, at the Department of Integrated Systems Engineering, the Ohio State University, USA. Until now, almost all of the works in the area of carbon emission reduction have been focused on the generation side. Although reducing emission in the generation side may indirectly reduce the carbon footprints in the demand side, lack of smart control on consumers' carbon footprint is a great shortcoming in demand side. In this project, in order to address this existing gap, a demand side management-based model is investigated. The main idea of this project is to propose a model that works based on a smart communication with consumers. After a joint online carbon footprint and price allocation procedure, the consumers know not only the price of energy that they use but also the amount of induced carbon by their activity in a given time frame. To make a proper communication, a joint price- and carbon footprint-responsive demand model, which plays an important role, is investigated. It is assumed that demand responsiveness is enabled by real-time allocations. The demand side management via this novel standpoint may result in avoiding surcharge in electricity bills and reducing both carbon emissions and electric power demands. In order to have a more applicable model, an environmentally constrained active-reactive optimal power flow (ECAROPF) considering disjoint constraints (such as prohibited operating zone) is taken into consideration. In this regard, implementing the ECAROPF via The General Algebraic Modeling System (GAMS) is investigated where its solvability by commercial solvers makes it an even more applicable tool. To verify the aforementioned models and considerations several IEEE test systems are conducted and the results are considered in detail. (AU)

Scientific publications

(8)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

POURAKBARI-KASMAEI, MAHDI; LEHTONEN, MATTI; CONTRERAS, JAVIER; SANCHES MANTOVANI, JOSE ROBERTO. Carbon Footprint Management: A Pathway Toward Smart Emission Abatement. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, v. 16, n. 2, p. 935-948, FEB 2020. Web of Science Citations: 2.

POURAKBARI-KASMAEI, MAHDI; LEHTONEN, MATTI; FOTUHI-FIRUZABAD, MAHMUD; MARZBAND, MOUSA; SANCHES MANTOVANI, JOSE ROBERTO. Optimal power flow problem considering multiple-fuel options and disjoint operating zones: A solver-friendly MINLP model. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, v. 113, p. 45-55, DEC 2019. Web of Science Citations: 5.

CERNA, FERNANDO V.; POURAKBARI-KASMAEI, MAHDI; CONTRERAS, JAVIER; GALLEGO, LUIS A. Optimal Selection of Navigation Modes of HEVs Considering CO2 Emissions Reduction. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v. 68, n. 3, p. 2196-2206, MAR 2019. Web of Science Citations: 5.

CERNA, FERNANDO V.; POURAKBARI-KASMAEI, MAHDI; ROMERO, RUBEN A.; RIDER, MARCOS J. Optimal Delivery Scheduling and Charging of EVs in the Navigation of a City Map. IEEE TRANSACTIONS ON SMART GRID, v. 9, n. 5, p. 4815-4827, SEP 2018. Web of Science Citations: 9.

HOME ORTIZ, JUAN MANUEL; POURAKBARI-KASMAEI, MAHDI; LOPEZ, JULIO; SANCHES MANTOVANI, JOSE ROBERTO. A stochastic mixed-integer conic programming model for distribution system expansion planning considering wind generation. ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS, v. 9, n. 3, SI, p. 551-571, AUG 2018. Web of Science Citations: 9.

MELGAR DOMINGUEZ, OZY D.; KASMAEI, MAHDI POURAKBARI; LAVORATO, MARINA; SANCHES MANTOVANI, JOSE R. Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems. ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS, v. 9, n. 3, SI, p. 529-550, AUG 2018. Web of Science Citations: 11.

POURAKBARI-KASMAEI, MANDI; SANCHES MANTOVANI, JOSE ROBERTO. Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, v. 97, p. 240-249, APR 2018. Web of Science Citations: 9.

POURAKBARI-KASMAEI, MANDI; CONTRERAS, JAVIER; SANCHES MANTOVANI, JOSE ROBERTO. A demand power factor-based approach for finding the maximum loading point. Electric Power Systems Research, v. 151, p. 283-295, OCT 2017. Web of Science Citations: 3.