Medium-term planning of active distribution systems considering voltage-dependent loads, network reconfiguration, and CO2 emissions

Mejia, Mario A.; Macedo, Leonardo H.; Muñoz-Delgado, Gregorio; Contreras, Javier; Padilha‐Feltrin, Antonio

doi:10.1016/j.ijepes.2021.107541

Cited by 25 publications

(8 citation statements)

References 34 publications

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“…Risk is assessed from two perspectives: generation cost fluctuation and carbon emissions. Risk related to environmental aspects is transformed into a monetary term using carbon taxes, a cost-based tool that establishes a tax per ton of carbon emissions [6].…”

Section: Problem Formulationmentioning

confidence: 99%

“…Investment costs are determined by (5) and include investments in substations, lines, WT units, PV units, EVCSs, and ESSs, respectively. Operational costs are calculated by (6). The first term in (6) represents the energy supplied by substations; the second and third terms correspond to the operation and maintenance costs (O&M) of WT and PV units, respectively; the fourth and fifth terms represent the ESS operational costs.…”

Section: B Objective Functionmentioning

confidence: 99%

“…Operational costs are calculated by (6). The first term in (6) represents the energy supplied by substations; the second and third terms correspond to the operation and maintenance costs (O&M) of WT and PV units, respectively; the fourth and fifth terms represent the ESS operational costs. Finally, the carbon tax (𝐶𝑇𝑋) is determined by (7).…”

Section: B Objective Functionmentioning

confidence: 99%

“…In [5], the long-term DSEP has been solved through a hybrid approach based on classical optimization methods and metaheuristics. Such a proposal addresses the allocation of DG units and ESS as in [6]. A multi-objective model that aims to minimize carbon emissions and investment and operational costs is proposed in [7].…”

Section: Introductionmentioning

confidence: 99%

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Reactive power by the substation 𝑖 at bus 𝑑, scenario 𝑠, and period 𝑝 𝑄 @,-,% >?Reactive power injected by WT at bus k, scenario s, and period 𝑝. 𝑉 ',-,% (CD Square of the voltage at bus 𝑖, scenario 𝑠, and period 𝑝. 𝑧 '1,5,% Operational variable associated with line 𝑖𝑗, conductor 𝑎, at period 𝑝. Integer and binary variables: 𝑁 7,% )* Integer variable that indicates the number of ESS at bus 𝑏 and period 𝑝. 𝑁 F,3,% )8 Integer variable that indicates the number of EV chargers at bus 𝑟, type 𝑐 and period 𝑝. 𝑁 :,% ;< Integer variable that indicates the number of PV unit at bus 𝑢 and period 𝑝. 𝑥 F,% )8 Investment variable for installing an EVCS at bus 𝑟 and period 𝑝. 𝑥 '1,5,% 9 Binary variable for investment in line ij using conductor type 𝑎, and period 𝑝. 𝑥 /,% * Binary variable for construction of substation at bus 𝑑 and period 𝑝. 𝑥 @,% >?Binary variable for allocation a WT unit at bus 𝑘 and period 𝑝.

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Section: Problem Formulationmentioning

confidence: 99%

Section: B Objective Functionmentioning

confidence: 99%

Section: B Objective Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Risk-Based Planning Approach for Sustainable Distribution Systems Considering EV Charging Stations and Carbon Taxes

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Soares

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et al. 2023

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“…Traditionally, the planning optimization and operation optimization of the distribution network are independently executed, and the operation optimization is carried out after the planning optimization. When renewable energy sources or energy storage equipment are connected to the distribution network, the operation mode of these equipment will affect the transmission losses of the grid and operation mode of the equipment (Ashoornezhad et al, 2021;Koutsoukis and Georgilakis, 2022;Mejia et al, 2022). Therefore, the traditional separated planning method cannot guarantee optimal results.…”

Section: Introductionmentioning

confidence: 99%

Planning and Operation of Hybrid Renewable Energy Systems

2022

Frontiers Research Topics

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Nonlinear active distribution network optimization for improving the renewable energy power quality and economic efficiency: a multi-objective bald eagle search algorithm

Tseng

Wang

et al. 2023

Soft Comput

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Medium-term planning of active distribution systems considering voltage-dependent loads, network reconfiguration, and CO2 emissions

Cited by 25 publications

References 34 publications

A Risk-Based Planning Approach for Sustainable Distribution Systems Considering EV Charging Stations and Carbon Taxes

A Risk-Based Planning Approach for Sustainable Distribution Systems Considering EV Charging Stations and Carbon Taxes

Planning and Operation of Hybrid Renewable Energy Systems

Nonlinear active distribution network optimization for improving the renewable energy power quality and economic efficiency: a multi-objective bald eagle search algorithm

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