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High scale integration of renewable energies has led power system towards a new set of challenges that have increased the complexity of cost optimization problem. Moreover, forecast errors in the prediction of wind, PV and load affect the accuracy of optimization. Therefore, cumulants and Gram–Charlier method have been proposed for solving probabilistic load flow (PLF)-based optimal transmission switching (OTS) for large-scale integration of renewable energy. The cumulants method has been used for forecast error evaluation in order to improve the accuracy of the proposed method. Moreover, Gram–Charlier method has been utilized for PLF-based OTS evaluation due to its fast convergence. In this paper, the simultaneous optimization of generation dispatch and network topology for PLF-based OTS has been investigated. Wind farm along with PV has been considered for large-scale integration. The proposed approach has been applied on IEEE 118 bus system with renewable integration. The results depict that the proposed approach is quite useful for large-scale power systems.

The steady-state performance of modular multilevel converter (MMC) can be optimized by the following methods: circulating current injection, third-harmonic signal injection, and average capacitor voltage control. However, most of the papers, due to the deficiencies of their MMC models, are limited to the study of adopting just one method and only optimizing a single-aspect of the performance. Thus, this article proposes a general MMC model for the comprehensive study of the steady-state performance optimization. The general model is built based on an equilibrium equation between the internal quantities and the external quantities of the MMC. This general model is capable of analyzing the optimization where the optimizing methods are combined and used to improve the multiaspect performance of the MMC. In addition, more influence factors are taken into account; hence, the calculation error can be smaller than 1% and even the minor effect of each optimizing method can be reflected. The proposed model is compared with traditional models; and it is found that both dc and fundamental components in modulation signals will be affected by the injected circulating current, rather than the constant values in the traditional models. Finally, the proposed MMC model is verified by both simulation and experiment.

The capacitance of sub-module capacitor has a great impact on the cost, size, and operation of the modular multi-level converter (MMC). However, the capacitance selected by the existing methods does not always meet the requirement in practice. To find out the reasons for this improper selection, the existing selection methods are analyzed in this paper. Based on the analysis, a new capacitance-selection method is proposed. In the new method, the problems of the existing methods are solved, and the calculation of capacitor voltage is based on a proposed capacitor-voltage model whose calculation error can be smaller than 0.1%. Furthermore, the Secant Method is used in the capacitance selection to quickly calculate the required capacitance. The new capacitance-selection method can be applicable to the MMC not having a circular operating region. In addition, this paper found that the capacitor voltage and the capacitor-voltage ripple reach their maximum values when the power-factor angles of the MMC are –π/2 and π/2, respectively, and the dc component in the capacitor voltage changes according to the operating condition of the MMC. Finally, the proposed selection method and theoretical analyses are verified by both simulation and experiment.

In this paper, a model is proposed for the optimal operation of multi-energy microgrids (MEMGs) in the presence of solar photovoltaics (PV), heterogeneous energy storage (HES) and integrated demand response (IDR), considering technical and economic ties among the resources. Uncertainty of solar power as well as the flexibility of electrical, cooling and heat load demand are taken into account. A p-efficient point method is applied to compute PV power at different confidence levels based on historical data. This method converts the uncertain PV energy from stochastic to deterministic to be included in the optimization model. The concept of demand response is extended and mathematically modeled using a linear function based on the quantized flexibility interval of multi-energy load demand. As a result, the overall model is formulated as a mixed-integer linear program, which can be effectively solved by the commercial solvers. The proposed model is implemented on two typical summer and winter days for various cases. Results of case studies show the important benefits for maximum PV utilization, energy efficiency and economic system operation. Moreover, the influence of the different confidence levels of PV power and effectiveness of IDR in the stochastic circumstances are addressed in the optimization-based operation.

This paper presents static synchronous compensator (STATCOM) integration into a doubly-fed induction generator (DFIG) based wind park (WP), analyses the impact of STATCOM on the WP high voltage ride-through (HVRT) capability, and proposes a transient function for the STATCOM to improve the WP HVRT capability. An actual WP is adopted as a test system. The STATCOM size is selected considering the grid code requirement for power factor control, and various wind turbine (WT) and medium voltage (MV) feeder outage scenarios. The WP HVRT capability is assessed with electromagnetic transient (EMT) simulations by analyzing the responses to a parametric voltage waveform. The external system is represented by a Thevenin equivalent. The pre-described voltage waveforms are applied to the Thevenin source in order to assess the conformity of the HVRT capability to Hydro-Quebec specifications. The WP simulation model includes all details regarding collector grid and overvoltage protection. The simulation results demonstrate that, STATCOM usage provides a noticeable improvement in HVRT capability of the WP, especially with the proposed transient function.

There is an increasing interest in low voltage direct current (LVDC) distribution grids due to advancements in power electronics enabling efficient and economical electrical networks in the DC paradigm. Power flow equations in LVDC grids are non-linear and non-convex due to the presence of constant power nodes. Depending on the implementation, power flow equations may lead to more than one solution and unrealistic solutions; therefore, the uniqueness of the solution should not be taken for granted. This paper proposes a new power flow solver based on a graph theory for LVDC grids having radial or meshed configurations. The solver provides a unique solution. Two test feeders composed of 33 nodes and 69 nodes are considered to validate the effectiveness of the proposed method. The proposed method is compared with a fixed-point methodology called direct load flow (DLF) having a mathematical formulation equivalent to a backward forward sweep (BFS) class of solvers in the case of radial distribution networks but that can handle meshed networks more easily thanks to the use of connectivity matrices. In addition, the convergence and uniqueness of the solution is demonstrated using a Banach fixed-point theorem. The performance of the proposed method is tested for different loading conditions. The results show that the proposed method is robust and has fast convergence characteristics even with high loading conditions. All simulations are carried out in MATLAB 2020b software.

With the increasing integration of rooftop photovoltaic (PV) generation and plug-in electric vehicles (EVs) into the households at user level, household consumers become prosumers. The coordination between the household prosumers and distribution network (DN) becomes essential to the energy management and optimal operation for both entities. In this paper, the residential prosumer cluster is considered as a residential microgrid (RMG) and a hierarchical DN integration method for the multi-RMGs is presented. A two-level hierarchical distributed optimization model is established based on the analytical target cascading to coordinate the RMGs and DNs. At the RMGs level, each RMG is required to individually optimize the energy consumption scheduling in every household by taking into account the effect of time-of-use electricity price on the demand response of EVs and flexible loads. At the DN level, the optimally coordinated operation problem is formulated as a relaxed optimal power flow model based on the second order cone programming by considering the power flow balance constraints. Case studies on the modified IEEE 33-bus system demonstrate the feasibility and effectiveness of the proposed method by achieving coordinated economic optimality as well as coordinated operating points for all entities.