PI control and model predictive control (MPC) are mainly utilized in battery and supercapacitor hybrid energy storage system (HESS) of DC microgrid. Unfortunately, the regulation time of PI controller is long, while large current ripples are introduced by MPC when the system frequency is low. This paper proposes a new model predictive current control (new MPCC) strategy for HESS based on MPC and PI controllers. This method reduces current ripples, and meanwhile enhances system stability and rapidity. MPC is adopted as the outer loop, and calculates reference values for the inner PI current loop. Furthermore, the state of charge (SOC) of the supercapacitor (SC) is considered based on fuzzy control to optimize the reference power of SC inner controller. Firstly, the topology and mathematical model of HESS in DC microgrid are analyzed. Then based on PI control and MPC, the new MPCC is proposed, and compared with MPC and PI methods respectively. Finally, the fuzzy control method takes SOC of SC into account to optimize the SC reference current. Simulation and experimental results show that the proposed new control strategy could effectively decrease current ripples and dynamic processes, and entirely perform high energy density characteristic of batteries and high power density characteristic of SC.

Reliability is of critical importance for the microgrid (MG) and deserved more attention. Aiming at photovoltaics (PV) and energy storage system (ESS) based MG, the microturbine (MT), PV, ESS and comprehensive load (CL) which is composed of hourly time-varying component, stochastic component, and controllable component, are chronologically modeled and combined with model of load shedding minimization and sequential Monte Carlo (SMC) simulation algorithm. Then, the reliability assessment framework is developed and employed in the comprehensive case studies. Firstly, varying characteristics of reliability indices, including loss of load probability (LOLP), average service availability index (ASAI), system average interruption duration index (SAIDI), system average interruption frequency index (SAIFI) and customer average interruption duration index (CAIDI), over PV penetration are investigated, and the surge effect of SAIFI (SE-SAIFI) is especially put forward and studied, followed by the principle of PV capacity decision considering SE-SAIFI. Secondly, the clear pictures of reliability profiles over ESS sizes are depicted and analyzed, following with a novel method to reasonably decide ESS sizes based on the definition of expected hourly redundant power (EHRP). At last, reliability indices of multiple scenarios with different percentages of controllable load are calculated and the benefits of load management are analyzed in the viewpoint of reliability of standalone MG. Results of the case studies also confirm the necessities of reliability assessment during the MG planning and size optimization, and the validity of the methodologies developed in this work.

In DC microgrids, a large-capacity hybrid energy storage system (HESS) is introduced to eliminate variable fluctuations of distributed source powers and load powers. Aiming at improving disturbance immunity and decreasing adjustment time, this paper proposes active disturbance rejection control (ADRC) combined with improved MPC for n + 1 parallel converters of large-capacity hybrid energy storage systems. ADRC is utilized in outer voltage control loops, and improved MPC is employed in inner current control loops of n battery converters. Droop control is adopted to obtain power distribution between n battery converters, and a DC bus voltage compensator is used to compensate voltage deviations and maintain constant DC bus voltage. The low-pass filter (LPF) is adopted to obtain high-frequency power as the reference for the supercapacitor converter, ADRC is also utilized in the outer power control loop, and MPC is employed in the inner current control loop. Compared with traditional observers, the voltage expansion state observer of the proposed ADRC control is independent of the system model and parameters and consequently has strong disturbance immunity, and significantly reduces voltage overshoots during power fluctuations. The MPC-based inner current control loops of n + 1 converters accelerate current response speed and significantly decrease switching losses. Simulation and experimental results indicate that utilizing the proposed control strategies, large-capacity HESS has stronger anti-interference ability, shorter regulation time, smaller switching loss, and simultaneously maintains the stability of the DC bus voltage.

With the increasing use of electric vehicles (EVs), EVs will be widely connected to the microgrid in the future. However, the influence of the disorderly charging behavior of EVs on the stable and reliable operation of the power grid cannot be ignored. To address these challenges, the charging load characteristic model is established to describe the charging behavior of EVs. Then, an EVs orderly charging strategy based on electricity price guidance is proposed, and the goal is to minimize the peak–valley difference ratio and the total cost of EV charging. The result shows that, compared with disorderly charging, the EV orderly charging strategy based on electricity price guidance proposed in this paper can effectively reduce the peaking and valley difference ratio of load, reduce user’s charging costs, and optimize the reliability level of the microgrid.

Islanded DC microgrids composed of distributed generators (DGs), constant power loads (CPLs), parallel converters, batteries and supercapacitors (SCs) are typical nonlinear systems, and guaranteeing large-signal stability is a key issue. In this paper, the nonlinear model of a DC microgrid with a hybrid energy storage system (HESS) is established, and large-signal stability criteria are obtained. The HESS consists of batteries and SCs. The derived criteria reveal the influences of the filter parameters, CPL power, DG power and the proportional control parameters of the battery converter and the SC converter on the system large-signal stability. Furthermore, important large-signal stabilization methods for regulating the HESS converter’s control parameters can easily achieve the large-signal stabilization of islanded DC microgrids without extra equipment. The paper is summarized as follows: First, the topology of and control strategy for a DC microgrid with an HESS and CPLs are proposed. Then, according to the characteristics of the HESS, the DGs and the CPLs, the system is equivalently simplified. Finally, the nonlinear model and large-signal stability criteria are both derived using the mixed potential theory, and a large-signal stabilization design method for the HESS converter’s control parameters is proposed. The experimental and simulation results show the effectiveness of the proposed large-signal stabilization method.

Due to the polymorphic uncertainties in microgrids (MGs), prohibitive computational burden is produced in reliability assessment. In this work, a novel sequential sampling algorithm (NSSA) compatible with sequential Monte Carlo (SMC) simulation is developed to overcome the computational burden. First, optimal probability density functions (PDFs) of random variables are worked out based on variation method. Then, optimal PDFs are employed to chronologically simulate the random states of microturbine (MT), photovoltaics (PV) and time varying load with improved computational efficiency. Therefore, the convergence of reliability assessment is accelerated accordingly. A series of case studies have been conducted, and the computational results show that NSSA provides a favorable sampling efficiency and adaptability to system conditions in reliability assessment of MGs. At last, based on optimal PDFs produced by NSSA, dominant joint PDF (DJ-PDF) is defined and employed to quantify the contributions of different scenarios to the reliability indices. Case studies have confirmed that DJ-PDF can provide detailed information for scenario-based reliability analysis.