The literature covering Plug-in Electric Vehicles (EVs) contains many charging/discharging strategies. However, none of the review papers covers such strategies in a complete fashion where all patterns of EVs charging/discharging are identified. Filling a gap in the literature, we clearly and systematically classify such strategies. After providing a clear definition for each strategy, we provide a detailed comparison between them by categorizing differences as follows: complexity; economics and power losses on the grid side; ability to provide ancillary services for integrity of the power grid; operation aspects (e.g., charging timing); and detrimental impact on the EV, the power grid, or the environment. Each one of these comparison categories is subdivided into even more detailed aspects. After we compare the EV charging/discharging strategies, we further provide recommendations on which strategies are suitable for which applications. Then, we provide ratings for each strategy by weighting all aspects of comparison together. Our review helps authors or aggregators explore likely choices that might suit the specific needs of their systems or test beds.

In the transportation sector, electric battery bus (EBB) deployment is considered to be a potential solution to reduce global warming because no greenhouse gas (GHG) emissions are directly produced by EBBs. In addition to the required charging infrastructure, estimating the energy consumption of buses has become a crucial precondition for the deployment and planning of electric bus fleets. Policy and decision-makers may not have the specific tools needed to estimate the energy consumption of a particular bus network. Therefore, many state-of-the-art studies have proposed models to determine the energy demand of electric buses. However, these studies have not critically reviewed, classified and discussed the challenges of the approaches that are applied to estimate EBBs’ energy demands. Thus, this manuscript provides a detailed review of the forecasting models used to estimate the energy consumption of EBBs. Furthermore, this work fills the gap by classifying the models for estimating EBBs’ energy consumption into small-town depot and big-city depot networks. In brief, this review explains and discusses the models and formulations of networks associated with well-to-wheel (WTW) assessment, which can determine the total energy demand of a bus network. This work also reviews a survey of the most recent optimization methods that could be applied to achieve the optimal pattern parameters of EBB fleet systems, such as the bus battery capacity, charger rated power and the total number of installed chargers in the charging station. This paper highlights the issues and challenges, such as the impact of external factors, replicating real-world data, big data analytics, validity index, and bus routes’ topography, with recommendations on each issue. Also, the paper proposes a generic framework based on optimization algorithms, namely, artificial neural network (ANN) and particle swarm optimization (PSO), which will be significant for future development in implementing new energy consumption estimation approaches. Finally, the main findings of this manuscript further our understanding of the determinants that contribute to managing the energy demand of EBBs networks.

Over the last few years, the number of grid-connected photovoltaic systems (GCPVS) has expanded substantially. The increase in GCPVS integration may lead to operational issues for the grid. Thus, modern GCPVS control mechanisms should be used to improve grid efficiency, reliability, and stability. In terms of frequency stability, conventional generating units usually have a governor control that regulates the primary load frequency in cases of imbalance situations. This control should be activated immediately to avoid a significant frequency variation. Recently, renewable distribution generators such as PV power plants (PVPPs) are steadily replacing conventional generators. However, these generators do not contribute to system inertia or frequency stability. This paper proposes a control strategy for a GCPVS with active power control (APC) to support the grid and frequency stability. The APC enables the PVPP to withstand grid disturbances and maintain frequency within a normal range. As a result, PVPP is forced to behave similar to traditional power plants to achieve frequency steadiness stability. Frequency stability can be achieved by reducing the active power output fed into the grid as the frequency increases. Additionally, to maintain power balance on both sides of the inverter, the PV system will produce the maximum amount of active power achievable based on the frequency deviation and the grid inverter’s rating by working in two modes: normal and APC (disturbance). In this study, a large-scale PVPP linked to the utility grid at the MV level was modeled in MATLAB/Simulink with a nominal rated peak output of 2000 kW. Analyses of the suggested PVPP’s dynamic response under various frequency disturbances were performed. In this context, the developed control reduced active power by 4%, 24%, and 44% when the frequency climbed to 50.3 Hz, 50.8 Hz, and 51.3 Hz, respectively, and so stabilized the frequency in the normal range, according to grid-code requirements. However, if the frequency exceeds 51.5 Hz or falls below 47.5 Hz, the PVPP disconnects from the grid for safety reasons. Additionally, the APC forced the PVPP to feed the grid with its full capacity generated (2000 kW) at normal frequency. In sum, the large-scale PVPP is connected to the electrical grid provided with APC capability has been built. The system’s capability to safely ride through frequency deviations during grid disturbances and resume initial conditions was achieved and improved. The simulation results show that the given APC is effective, dependable, and suitable for deployment in GCPVS.

The incorporation of distributed generation (DG) units in distribution network voltage control may create operational conflicts with other conventional voltage control devices. Structural changes of networks can also increase the possibility to create control interactions. Control rules-based voltage control methods are not suitable for large scale networks where large number of control choices are available. Similarly, optimization-based voltage control methods are impractical to implement since many control variables have to be used to obtain the optimal solution. Therefore in this paper, a new technique for choosing a global group of the most effective control variables considering the ones with low cost is proposed for voltage regulation in distribution networks. This technique is based on the concept of electrical distances between the voltage control devices and network nodes to derive a correction index (CI). The index represents the level of effectiveness of each control variable with respect to all violated voltages. The index is implemented in two phase algorithms (top-down and bottom-up) to identify the global group of control variables. The proposed technique takes into consideration five aspects: the effectiveness, availability, and cost of the control variables as well as the structural changes of networks and the coordination between control variables to simultaneously eliminate the violation in the voltages. The technique is fast and suitable to be implemented for online voltage control. The proposed method is successfully examined on the modified IEEE 123 distribution system under different scenarios.

Interfacing a weak grid imposes challenges on distributed generators (DGs). These challenges include transient frequency and voltage dynamics that can destabilize the system. Accordingly, this paper investigates the grid stiffness based on different scenarios and the dynamics of a grid feeding DG connected to a weak grid. Moreover, the dynamic effects of the physical and control parameters on the system’s stability are deeply analyzed and evaluated. Specifically, complete mathematical models and graphical representation are carried out to precisely examine the impact of the system parameters on the stability and performance of the DG. Therefore, stable deployment of renewable energy resources into power networks can be achieved as well as an efficient and robust performance of DGs can be ensured when connected to weak grids. The obtained results show the importance of the performed study in optimal sizing and designing the output filter of the inverter and the impact of tuning the control parameters on the system dynamics. As a result, a proper design of system physical and control parameters can be accurately achieved considering all factors affect the system performance. The paper also conducts detailed and elaborated analyses and simulations to evaluate the performance of a PI-controlled RC damped inverter connected to a weak grid. The proposed filter design of the interfacing inverter can significantly extend the integration of DGs into microgrids without requiring complex control schemes or oversized components.

The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might be created, and other solutions are required. Many researchers tried to solve the problem; however, limitations exist because of the decentralized topology of the network. The system operator is not allowed to control the end-users’ load due to security and privacy issues. To overcome this situation, we propose a novel data-energy management algorithm on the transformer’s level that controls the power demand profiles of the householders and exchange energy between them without violating their privacy and security. Our method is compared to an existing one in the literature based on a decentralized control strategy. Simulations show that our approach has reduced the electricity cost of the end-users by 3%, increased the revenue of the system operator, and reduced techno-economic losses by 50% and 42%, respectively. Our strategy shows better performance even with a 100% penetration level of EVs on the network, in which it respects the network’s constraints and maintains the voltage within the recommended limits.