Joint PEV Charging Network and Distributed PV Generation Planning Based on Accelerated Generalized Benders Decomposition

Abstract

Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-towheels greenhouse gas emissions, promote renewable power adoption and defer power system investments. This paper proposes a multidisciplinary approach to jointly planning PEV fast-charging stations and distributed photovoltaic (PV) power plants on coupled transportation and power networks. First, we develop models of 1) PEV fast-charging stations; 2) highway transportation networks under PEV driving range constraints; 3) PV power plants with reactive power control. Then, we formulate a two-stage stochastic mixed integer second order cone program (MISOCP) to determine the sites and sizes of 1) PEV fast-charging stations; 2) PV power plants. To address the uncertainty of future scenarios, a significant number of future typical load, traffic flow and PV generation curves are adopted. This makes the problem large scale. We design a Generalized Benders Decomposition Algorithm to efficiently solve it. To the authors' knowledge, this work is the first that jointly plans both PEV fast-charging stations and PV plants with consideration for PEV driving range limits and reactive PV power control. We conduct numerical experiments to illustrate the effectiveness of the proposed method, and validate the benefits of the joint planning and adopting advanced PV reactive power control.

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

“…For example, choosing different uncertainty sets for r-LAPB could take advantage of strong correlation among some loads. Future works also include designing approximation algorithms with optimality guarantees and exploring the benefits of controlling distributed generations [39][40][41], electric vehicles [42][43][44], energy storage [29,[45][46][47] and demand response [48][49][50][51].…”

Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

“…However, the output of PV power plant is volatile. A two-stage stochastic MISOCP model is offered in [59] to determine the optimal size of charging stations and PV generators. In practice, an entirely accurate probability distribution of uncertain factor is difficult to acquire.…”

Multi-objective simultaneous optimal planning of electrical vehicle fast charging stations and DGs in distribution system

“…In recent literature, there are two papers considered the simultaneous optimal planning of CSs and DG power unit in the distribution system. The first one [21] is joint planning of EVCS and distributed photovoltaic generation in the distribution system is solved by using an accelerated generalized Benders decomposition algorithm. A multidisciplinary approach is proposed with the account of investment cost (the fixed cost of EVCS and PV power plant, variable cost for adding an extra charging spot in EVCS and per unit PV panel in PV power plant) and maintenance cost (the cost of electricity, penalty for unsatisfied PEV charging demand and penalty for undesirable voltage deviation), in order to identify the location and size of EVCS and PV plant.…”

“…In the majority of previous work, the authors consider the optimal placement of CSs only, it strongly affects distribution system power losses and voltage profile. Only a few papers [21,22] the authors considered the simultaneous optimal planning of CSs and DG power units in distribution system but in those papers does not consider the specific energy consumption of EV user loss, voltage deviation, investment and maintenance cost of CS and DG power units.…”