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Traditional droop control strategy has lack of the decoupling ability, so the efficiency and stability of the microgrid based on the traditional droop control strategy are easily affected by the uncontrollable coupling of the distributed generation (DG) units. In this paper, an improved droop control strategy incorporating the coupling compensation and virtual impedance is proposed to improve the efficiency and stability of the microgrid. Its coupling compensation comprises the angular frequency deviation compensation and voltage deviation compensation, which decreases the influence of the uncontrollable coupling. The virtual impedance can change the characteristics of the line impedance of the DG units and reduce their coupling. Therefore, the combination of the coupling compensation and virtual impedance can greatly reduce the power circulating-current of the microgrid and improve its dynamic performance. Then, an improved particle swarm optimization algorithm incorporating the multi-swarm and multi-velocity is taken to optimize the parameters of the coupling compensation with high accuracy and high reliability. Simulation and experimental results validate the high performance of the improved droop control strategy. [ABSTRACT FROM AUTHOR]

Traditional particle swarm optimization (PSO) algorithm mainly relies on the history optimal information to guide its optimization. However, when the traditional PSO algorithm searches high-dimensional complex problems, wrong position information of the best particles can easily cause the most of the particles move toward wrong space, so the traditional PSO algorithm is easily trapped into local optimum. To improve the optimization performance of the traditional PSO algorithm, an enhanced particle swarm optimization with multi-swarm and multi-velocity (MMPSO) is proposed. It comprises three particle swarms and three velocity update methods. The information sharing of the multi-swarm with various velocity update methods in the MMPSO can quickly discover more useful global information and local information, helping prevent particles from falling into local optimum and improving optimization precision of the algorithm. The MMPSO is tested on fourteen benchmark functions, and is compared with the other improved PSO algorithms. Comparison results validate the validity and feasibility of the MMPSO to optimize high-dimensional problems. [ABSTRACT FROM AUTHOR]

A novel droop control with coupling compensation and inertia is proposed for a microgrid to achieve high dynamic performance and stability of distributed generation units. The coupling compensation scheme consists of angular frequency deviation compensation and voltage deviation compensation. They can reduce the influence of uncontrolled power coupling. The inertia scheme consists of angular frequency inertia and voltage inertia. They can slow down the change rates of the angular frequency and voltage and reduce their fluctuation magnitudes. The combination of this novel droop control method and virtual impedance can help achieve accurate power sharing. An improved particle swarm optimization (PSO) algorithm with multiswarm and multivelocity (MMPSO) is also proposed to optimize the parameters of the coupling compensation and inertia with high precision and high reliability. A simulated model and experiment platform of a microgrid are set up for testing, and the simulation and experimental results validate the excellent performance of the MMPSO and the effectiveness of the novel droop control method. [ABSTRACT FROM AUTHOR]

The quasi- $Z$ source (qZS) cascaded multilevel inverter (CMI) (qZS-CMI) presents attractive advantages in application to photovoltaic (PV) power system. Each PV panel connects to an H-bridge qZS inverter (qZSI) to form a power generation module. The distributed maximum power point tracking and all modules' dc-link peak voltage balance can be achieved. However, it is the same with the conventional CMI that the second-harmonic ( $2\omega$) voltage and current ripples exist in each qZSI module. It is crucial for a qZS-CMI to design the reasonable qZS network parameters to limit the ripples within a desired range. This paper proposes an analytic model to accurately calculate the $2\omega$ voltage and current ripples of each qZSI module. A qZS impedance design method based on the built model is proposed to limit the $2\omega$ ripples of dc-link voltage and inductor current. Simulated and experimental results through using the designed 1.5-kW prototype validate the proposed analytic model and the design method. Furthermore, this paper analyzes all of the operating states for a qZSI module and calculates the power loss. The measured efficiency from the prototype verifies the theoretical calculation, and the qZS-CMI-based grid-tie PV power system is tested in practical. [ABSTRACT FROM PUBLISHER]

In order to reduce the impact of load power fluctuations on the power system and ensure the economic benefits of user-side energy storage operation, an optimization strategy of configuration and scheduling based on model predictive control for user-side energy storage is proposed in this study. Firstly, considering the cost and benefits of energy storage comprehensively, an energy storage configuration optimization model with the highest annualized net income as the goal is built to determine the parameters for configuring energy storage. Then, with the goal of maximizing the profit during the scheduling period, pre-month scheduling optimization model, day-ahead scheduling optimization model and intra-day scheduling optimization model are established. The goal of the pre-month scheduling optimization model is to determine the maximum monthly demand; part of the scheduling results in the day-ahead scheduling optimization model directly participate in the intra-day scheduling; the intra-day rolling optimization relies on the advantages of real-time feedback and closed-loop scheduling to smooth out power fluctuations caused by load forecast errors. Finally, the configuration and economic benefit of lithium iron phosphate batteries, lead-carbon batteries and sodium-sulfur batteries are analyzed and compared, and scheduling analysis is performed. The simulation results show that the proposed optimization method can cut peaks and fill valleys, ensure the economic benefits of users, and provide guidance for users to invest in energy storage. [ABSTRACT FROM AUTHOR]