Search

The integration of renewable energy (RE) sources is increasing day by day because of their permanent existence and the limited quantities of fossil fuels. One of the most promising RE sources is photovoltaic (PV) technology, which is developing quickly in many countries worldwide. PV cells generate electricity by converting the sunlight to DC voltage. PV arrays are installed in outdoor areas and on the rooftops of homes to be directly subjected to the sun. Consequently, they are frequently subjected to lightning strikes, which may cause damage to PV arrays, service interruption, and additional cost for PV replacement. Therefore, an adequate lightning protection system (LPS) must be installed to protect the PV panels. In addition, the transient performance of PV panels during lightning strikes must be analyzed well. This paper presents a comprehensive review of the superior modeling methods of PV systems during lightning strikes. In addition, the paper displays the different platforms to simulate the transient effects of lightning strikes on PV systems. The lightning transient effects on PV arrays are studied based on the system modeling to assess the recommended LPS designs studied in the literature. The paper also gives some recommendations about the modeling methods and protection of PV systems during lightning strike. [ABSTRACT FROM AUTHOR]

Renewables (i.e., solar and wind power) in the Nordic area have highly seasonal characteristics, which severely restrict the wide development of renewables since they can be excessive in summer but insufficient in winter with intermittent outputs. The conventional battery energy storage system (BESS) with short-term adjustment functionality cannot eliminate the seasonal imbalance of renewables. In this regard, a risk-based bi-level planning model is presented to maximize the hosting capacity (HC) of renewables through configuring seasonal hydrogen storage (SHS) and BESS. Specifically, the upper level applies a multi-objective scheme to maximize HC and minimize the investment cost simultaneously. In turn, the lower level is driven by maximizing the profits of the distribution system operator (DSO) with the implementation of price-based demand response (PBDR). Due to forecasting errors of renewables and load resulting from intermittent output and random behaviors, a stochastic programming (SP) method is developed to address and adapt multiple uncertain fluctuations. Moreover, the conditional value-at-risk (CVaR) is introduced to measure the effect of the risks raised by multiple uncertainties on system operation. Finally, numerical studies are employed to verify the effectiveness of the proposed model. Compared to the cases without considering PBDR and SHS, the total renewable energy HC in the proposed model is increased by 2.30 MW and 0.37 MW, respectively, while the yearly cost benefit of DSO is enhanced by 28063.2 US$ and 17823.7 US$, respectively. The promising results demonstrate the empowerment of SHS can promote the cross-seasonal consumption of renewables, effectively maximizing the HC and improving the economic operation of distribution systems. • The hydrogen storage system is considered in this work for the cross-seasonal balance of renewables. • A bi-level planning model is proposed to improve hosting capacity and economic operation of the system. • The coordinated operation of seasonal hydrogen storage, demand response, and battery storage is designed. • The uncertainties and the operation risk brought by renewables and load are considered. [ABSTRACT FROM AUTHOR]

• Analysing circuit principle of harmonic source of nonlinear equipment. • Studying the harmonic source of ferromagnetic saturation devices. • Evaluating working characteristics of impact load equipment like arc furnace. • Discussing harmonic emission level of electric locomotive in different working conditions. • The causes of harmonics are explained from the physical level. The future of power systems is moving towards a greater use of renewable energy sources and a higher proportion of power electronic devices. However, this has led to an increase in power quality issues that can seriously affect the stable operation of power systems. One key aspect of evaluating power quality of the grid is analysing harmonics and their sources. There are several challenges in understanding and controlling harmonics, including modelling the sources of harmonics, tracing them, and controlling their impact. This paper presents a comprehensive review on the common models of harmonic sources in modern power systems, and provides insight into the circuit mechanisms, mathematical models, and operational processes of these sources. It also examines the harmonic characteristics of various sources in typical operating scenarios, involving typical residential power load, electric vehicle charging scenario, frequency conversion speed regulating device, renewable energy generation scenario, electric arc furnace load and electric locomotive load, and offers a summary of typical harmonic source equipment. Additionally, this paper looks ahead at the future and development directions of harmonic analysis and control in the context of modern power systems. This work can be used as a guide to improve the understanding of harmonic distortion in modern power systems and to develop methods for mitigating its negative effects on power quality and system stability. [ABSTRACT FROM AUTHOR]

Currently, distribution systems are continuously evolving towards modern and flexible structures while integrating promising renewable energy resources (RERs). In this regard, an optimal network constraint-based expansion planning model combined with an optimal integration framework of intermittent RERs is proposed in this work to improve the topological flexibility in modern distribution networks (DNs). Specifically, the best investment locations and times of substations, lines, and RER-based distributed generations (DGs) are jointly taken into consideration. Additionally, the uncertainty-based multiple scenarios are modeled by probability distribution functions to strengthen the robustness and reliability of DNs influenced by the stochastic of renewable energy and load behavior. The novel network constraint is combined with three levels, where the first level introduces the graph theory to guarantee the radiality topology of modern DNs. In the second level of the network constraint, graph theory and fictitious load theory are collaboratively applied to ensure that each subsystem has a reserve connection interconnected to other subsystems. The third level is modifying the conventional fictitious load theory to ensure each subsystem is linked with at least one DG. The proposed planning model is driven by the minimum present value of total cost, including investment cost of branches, DGs, and substations, cost of substations operation, the electricity purchasing cost of substations and DGs, power losses cost, and environmental penalty cost of conventional generators. Numerical results are presented to verify that a more flexible and resilient topology of the DN system is obtained, and criteria evaluation is introduced to validate its higher performance with respect to existing procedures from power supplied quality, environmental burden, and supplied flexibility three aspects. [ABSTRACT FROM AUTHOR]

Achieving the goal of sustainable development is dependent on the widespread integration of renewable energy sources, energy storage systems (ESSs), and electric vehicles (EVs). However, a continuous increase in the penetration of such elements would bring more complexities to the distribution network. Accordingly, this paper presents a unified planning model comprising renewable energy-based distributed generation (DG), ESS, and electric vehicle charging stations (EVCSs). In this regard, a Latin Hypercube Sampling method is utilized to generate multi-scenario for describing the uncertainty of renewable energy and load demand. The stochastic EV charging behaviors are represented by various probability density functions (PDF). In addition, an exploitable capacity loss of ESS and EV batteries is calculated by the battery degradation model based on the depth of discharge (DOD). Furthermore, the battery degradation cost is incorporated into the objective of the planning model to identify the optimal decision for candidate assets. A piecewise linearization approach is introduced to convert the problem into a mix-integer linear programming (MILP) model. Numerical results demonstrate that the exploitable capacity loss of batteries plays a key role in asset planning and provides potential contributions to the optimal decisions of the distribution network. In the meantime, by considering battery degradation in the optimization model, the sustainability and lifetime of the battery can be preserved. • Uncertainties include the renewable energy, load demand, and behaviors of electric vehicles are considered. • Renewable energy-based DG, ESS, and EVCS are involved in the unified planning model. • The degradation model is proposed to analyze the exploitable capacity loss of ESS and EV battery. • The enhancement of investment decision while maintaining the lifetime of battery is achieved. [ABSTRACT FROM AUTHOR]