Smart Grid
B.A. Usmanovich; T.M.H. Kinanah; A.H.O. Al-Mansor; K. Al-Majdi; S.H. Hlail; D.A. Lafta; A.R.T. Zaboun; J.K. Abbas
Abstract
The optimum location of electric vehicle (EV) parking lots is critical in distribution network design for lowering costs, boosting revenues, and enhancing dependability. However, conventional distribution network schedulers were not designed with these variables in mind. Furthermore, the increased use ...
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The optimum location of electric vehicle (EV) parking lots is critical in distribution network design for lowering costs, boosting revenues, and enhancing dependability. However, conventional distribution network schedulers were not designed with these variables in mind. Furthermore, the increased use of EVs for environmental reasons mandates the planning of EV parking spaces. As a result, distribution network designers must examine network technical difficulties, design approaches, and changing consumer needs. The placement of dispersed manufacturing resources and EV parking without sufficient planning and ideal location leads in economic challenges for investors and technical concerns for the network. As a result, future distribution networks should prioritize the ideal placement of EV parking lots and distributed production resources in order to maximize network capabilities and meet the needs of companies and power applications in the digital society. According to the findings, the rate of EV parking installations is very high. When power consumers remain connected to the grid during peak hours, distribution businesses benefit significantly, and the overall voltage profile improves. Variations in electric vehicle (EV) battery capacity, power cost, EV adoption, and the weighting coefficients required for optimization will all have different outcomes. It is critical to precisely determine the battery capacity of electric vehicles (EVs) as well as the efficiency of inverters in order to produce more accurate results. According to the findings, increasing the number of parking lot for EVs in a network enhances the benefit from minimizing losses, and providing peak load significantly. So that using 2 parking lot for EVs in a network can increase the overall profit to 129%.
Smart Grid
H. Rashidizadeh-Kermani; H. R. Najafi; A. Anvari-Moghaddam; J. M. Guerrero
Abstract
Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain ...
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Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain optimal decision making of an EV aggregator. To deal with mentioned uncertainties, the aggregator’s risk aversion is applied using conditional value at risk (CVaR) method in the proposed model. The proposed two-stage risk-constrained decision-making problem is applied to maximize EV aggregator’s expected profit in an uncertain environment. The aggregator can participate in the future and pool market to buy the required energy of EVs and offer optimal charge/discharge prices to the EV owners. In this model, in order to assess the effects of EVs owners’ reaction to the aggregator’s offered prices on the purchases from electricity markets, a sensitivity analysis over risk factor is performed. The numerical results demonstrate that with the application of the proposed model, the aggregator can supply EVs with lower purchases from markets.
Smart Grid
Hamidreza Arasteh; Mohammadsadegh Sepasian; Vahid Vahidinasab
Volume 3, Issue 2 , December 2015, , Pages 116-130
Abstract
This paper presents a novel concept of "smart distribution system expansion planning (SDEP)" which expands the concept of demand response programs to be dealt with the long term horizon time. The proposed framework, integrates demand response resources (DRRs) as virtual distributed generation (VDG) resources ...
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This paper presents a novel concept of "smart distribution system expansion planning (SDEP)" which expands the concept of demand response programs to be dealt with the long term horizon time. The proposed framework, integrates demand response resources (DRRs) as virtual distributed generation (VDG) resources into the distribution expansion planning. The main aim of this paper is to develop and initial test of the proposed model of SDEP to include DRRs which are one of the most important components to construct smart grid. SDEP is modeled mathematically as an optimization problem and solved using particle swarm optimization algorithm. The objective function of the optimization problem is to minimize the total cost of lines’ installation, maintenance, demand response persuasion, energy losses as well as reliability. Furthermore, the problem is subject to the constraints including radiality and connectivity of the distribution system, permissible voltage levels, the capacity of lines, and the maximum penetration level of demand response. Based on two sample test systems, the simulation results confirmed that the consideration of DRRs simultaneously with distribution system expansion can have economical profit for distribution planners.
