This paper presents a planning model that utilizes mobile energy storage systems (MESSs) for increasing the connectivity of renewable energy sources (RESs) and fast charging stations (FCSs) in distribution systems (DSs). The proposed planning model aims at enabling high penetration levels of green technologies while minimizing the total DS cost that includes investment, operating, and emission costs. The proposed model determines the optimal MESS sizes and transportation schedules as well as the optimal sizes and locations of wind-based distributed generators (DGs), photovoltaic (PV) DGs, and FCSs. The model takes into account techno-economic and environmental factors in addition to the power variations of RESs, FCSs, and load demands. The proposed planning model is applied on two benchmark test systems (i.e., 33-bus and 69-bus DSs). To evaluate the efficacy of the proposed model, the results obtained from the model are compared to those obtained from a traditional planning technique. The comparison of the results demonstrates that the proposed model with MESSs successfully achieves a significant cost saving and increases the penetration levels of RESs and FCSs.

The emerging interest in deployment of plug-in electric vehicles (PEVs) in distribution networks represents a great challenge to both system planners and owners of PEV-parking lots. The owners of PEV-parking lots might be interested in maximizing their profit via installing charging units to supply the PEV demand. However, with stringent rules of network upgrades, installing these charging units would be very challenging. Network constraints could be relaxed via controlling the net demand through integrating distributed generation (DG) and/or storage units. This paper presents an optimization model for determining the optimal mix of solar-based DG and storage units, as well as the optimal charging prices for PEVs. The main objective is to maximize the benefit of the PEV-parking lot’s owner without violating system constraints. Two cases are considered in this paper: uncoordinated and coordinated PEV demand. A novel mathematical model is further developed whereby the behavior of vehicles’ drivers, in response to different charging prices, is considered in generating the energy consumption of PEVs.

Renewable energy sources (RESs) and electric vehicle charging stations (EVCSs) have been extensively incorporated into distribution systems. Due to the stochastic nature of RES generation and electric vehicles (EVs), risky operational challenges might impact the grid. Therefore, this paper proposes a multi-objective planning framework to optimally allocate EVCSs in conjunction with RESs. Specifically, the proposed RESs and EVCSs planning framework considers three sub-objectives to be minimized, i.e., voltage deviations, energy losses, and EVs owners' dissatisfaction. Further, active power curtailment of RESs is precluded while considering the diverse operational constraints of the grid, RESs, and EVCSs. To provide further benefits, advanced control schemes of the interconnecting RES inverters, grid-to-vehicle (G2V), and vehicle-to-grid (V2G) schemes are considered in the proposed framework. A two-level approach is developed to solve this holistic framework with competing sub-functions to obtain the Pareto-optimal solutions. The outer optimization level precisely optimizes the RES locations and sizes, along with the optimal places of the EVCS. On the other hand, the inner level determines the optimal EVCS charging considering stochastic EV power, RES inverter reactive power, and the time-of-use energy tariff. The proposed framework has been tested on the 69-bus distribution system. The simulation results reveal the efficacy of the proposed RES and EVCS planning framework. The total voltage deviation and energy losses achieved by the proposed framework are reduced by 96% and 74%, respectively, with respect to the uncontrolled charging of EVs, while the owners' satisfactions are met.

Small wind turbines (SWTs) are promoted to be used in urban areas to mitigate the carbon footprint and expensiveupgrades expected from high penetration levels of fast charging stations (FCSs). In this paper, a planning framework is proposed to amplify the total benefit for the owners of FCSs and SWTs aswell as local distribution companies (LDCs). A stochastic program is developed to site and size SWTs along with FCSs in urban and suburban areas considering their specific wind characteristics,statutory regulations, turbine clustering studies, and geographic constraints. A worthiness metric is also proposed to rank FCS candidate locations based on their attractiveness to electric-vehicle(EV) drivers. An electric distribution network is overlaid onto ageographic map of downtown Chicago to assess the introduced planning framework. Results show that new efficient SWTs inurban areas can realistically justify their own investments overthe long-term, and reduce the overall system losses and support FCS loads. In the case study presented, the investments yield apresent value of $15M in profit, in 20 years, with an investment of$23M-only $6M of which is capital due in year one, while the rest consists of annual operation and maintenance costs.

Inverter-interfaced renewable energy sources (IIRESs) are typically controlled during fault conditions to meet fault ride-through (FRT) requirements, e.g., reactive current generation (RCG) requirements specified by grid codes (GCs). However, fault currents generated by inverters are different from the traditional sources, i.e., synchronous generators. Consequently, phase selection methods (PSMs) used by protection relays could suffer from erroneous fault type classification. This paper develops a dual current controller (DCC) that regulates the inverter's negative- and positive-sequence currents to simultaneously meet phase selection and RCG requirements. First, the negative-sequence-current angle is obtained based on the angles of both zero- and positive-sequence currents to enable a correct operation for phase selection. Then, the positive-sequence current angle is adjusted to reach a trade-off between RCG requirements and phase selection achieved by the negative-sequence current. Lastly, the reference currents of the IIRES are generated in the stationary frame without violating the inverter's current limits. The proposed DCC supports the grid voltage by meeting the RCG requirements and enhancing the grid reliability and resilience by enabling correct phase selection. Comprehensive time-domain and real-time simulation verify the precise operation of the proposed DCC under various fault conditions and GCs.