Toward Small Scale Renewable Energy Hub-Based Hybrid Fuel Stations: Appraising Structure and Scheduling

Faridpak, Behdad; Alahyari, Arman; Farrokhifar, Meisam; Momeni, Hosna

doi:10.1109/tte.2020.2972382

Cited by 29 publications

(17 citation statements)

References 31 publications

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“…The method described in the said paper is based on using the electricity distribution network. Paper [18] provides an analysis of the sites chosen for hybrid stations using renewable energy sources. The charging stations subject to the study are designed for both electric vehicles and natural gas vehicles.…”

Section: Overview Of the Methods Used For Optimal Siting Of Charging mentioning

confidence: 99%

Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

2020

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Development of electromobility in urban areas requires an appropriate level of vehicle charging infrastructure. Numerous methods for siting of charging stations have been developed to date, and they appear to be delivering diverse outcomes for the same area, which is why local authorities face the problem of choosing the right station layout. The solution proposed in this article is to use a travel planner to evaluate the distribution of charging stations over the area of a metropolis. The decision making support is achieved by determining optimal travel routes for electric vehicles according to their initial state of charge for the three selected station siting methods. The evaluation focused on the following three aspects: (1) number of travels that cannot be made (due to the lack of a charging station at a certain distance around the start point), (2) extension of the travel caused by the need to recharge the vehicle on-route, and (3) additional energy consumption by electric vehicles required to reach the charging station (necessity of departing from the optimal route). An analysis of the results has made it possible to determine a solution which is superior to others. For the case study analysed in the paper, i.e., the territory of the Metropolis of Upper Silesia and Dabrową Basin (Górnośląsko-Zagłębiowska Metropolia, GZM), the distribution of charging stations established in line with method I has returned the best results. What the method in question also makes possible is to indicate a safe minimum energy reserve to complete the travel by eliminating situations of unexpected vehicle immobilisation due to on-route energy depletion and by minimising the phenomenon referred to as range anxiety.

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Section: Overview Of the Methods Used For Optimal Siting Of Charging mentioning

confidence: 99%

Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

2020

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“…Step 2.1: Realization based on 2m þ 1 point estimated method. The 2m þ 1 PEM approach is utilized for uncertainty incorporating [19]. Mathematically, the deterministic operation cooptimization of IPGS which is using MINLP method can be expressed as (7a).…”

Section: Solution Methodologymentioning

confidence: 99%

“…Secondly, with the approximate nonlinearity approach, the stochastic operation of IPGS is optimized with incorporating risk analysis in which uncertainty variables cause a scenario-based analysis. To discuss uncertainties and to associate risk analysis, the scenarios were generated by 2m þ 1 point estimated method (PEM) [19]. The conditional value-at-risk (CVaR) is employed to analyze the financial risk of IPGS.…”

Section: Introductionmentioning

confidence: 99%

A series multi-step approach for operation Co-optimization of integrated power and natural gas systems

Faridpak

Farrokhifar

Murzakhanov

et al. 2020

Energy

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Power to gas units and gas turbines have provided considerable opportunities for bidirectional interdependency between electric power and natural gas infrastructures. This paper proposes a series of multi-step strategy with surrogate Lagrange relaxation for operation co-optimization of an integrated power and natural gas system. At first, the value of coordination capacity is considered as a contract to avoid dysfunction in each system. Then, the uncertainties and risks analysis associated with wind speed, solar radiation, and load fluctuation are implemented by generating stochastic scenarios. Finally, before employing surrogate Lagrange relaxation, the non-linear and non-convex gas flow constraint is linearized by two-dimension piecewise linearization. In the proposed procedure, constraints for energy storages and renewable energy sources are included. Two case studies are employed to verify the effectiveness of the proposed method. The surrogate Lagrange relaxation approach with coordination branch & cut method enhances the accuracy of convergence and can effectively reduce the decisionmaking time.

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“…In recent years, environmental issues such as global warming and increasing pollution have fostered solutions such as renewable generations [1][2][3]. Some of these renewables acting as distributed generators are rapidly proliferating in current distribution systems.…”

Section: Nomenclaturementioning

confidence: 99%

Hybrid uncertainty‐based offering strategy for virtual power plants

Alahyari

Ehsan

Pozo

et al. 2020

IET Renewable Power Generation

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This study proposes an optimal day-ahead (DA) electricity market offering model for a virtual power plant (VPP) formed by a mix of renewable distributed energy resources along with energy storage, such as electric vehicles. Two sources of uncertainty are considered, namely, wind power generation, modelled by an uncertainty set, and DA market price, modelled by scenarios. Opposite to classical robust optimisation approaches, the authors model maps minimal (worst-case) profits to a conservativeness parameter, while the classical robust optimisation maps conservativeness parameter to worst-case profits. In this regard, by using their optimisation framework, a VPP operator only deals with setting a minimum-profit constraint, which is more sensible and easy for interpretation, while the required conservativeness is endogenously determined. The proposed mathematical model for constructing the offering curve is a hierarchical four-level robust optimisation problem. The first level represents the optimal decision on the price-quantity offer bids; the second-and third-level relate to the optimal identification of conservativeness parameter; and the fourth-level represents the optimal operation of the VPP managed assets. The four-level model is reformulated as a single-level mixed-integer linear programming problem. The proposed approach and its applicability are verified using numerical simulations.

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Toward Small Scale Renewable Energy Hub-Based Hybrid Fuel Stations: Appraising Structure and Scheduling

Cited by 29 publications

References 31 publications

Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

A series multi-step approach for operation Co-optimization of integrated power and natural gas systems

Hybrid uncertainty‐based offering strategy for virtual power plants

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