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This article introduces an adaptive constrained generalized predictive controller (GPC) applied to a float interleaved boost converter (FIBC) with a low output current. FIBCs face uncertainties due to thermal effects in switches and diodes, variable operating frequencies, inductor losses, measurement errors, and load changes. The controller uses FIBC's direct duty cycle/output voltage model. It features constraints on the control signal and its variations, helping to regulate the input peak current. The controller's stability and performance under uncertainties are enhanced by three mechanisms: adaptive adjustment of control signal's upper constraint and the output error weight coefficient, and an online model estimation mechanism for the GPC. This includes constraining estimated model poles for assured closed-loop stability. Experimental results with 20% real uncertainties and load changes demonstrate the controller's effectiveness: it reduces input peak current, and output voltage oscillations, and overshoots by 3.5 A, 1 V, and 7.5%, respectively, compared to a basic constrained GPC.

Recent developments in renewable energy-based power systems and smart grids have brought challenges to designing new power conversion systems. On account of the intermittent nature of the renewable sources and unpredictability of the load demand, a combination of two or more energy sources and auxiliary storage systems is usually mandatory to meet the load demand, improve dynamic and steady-state characteristics, and reliability and availability of the system. Conventionally, SISO (single-input-single-output) DC/DC converters are arranged in parallel at a common DC bus to exchange power. In this scheme, separate conversion stages are employed for respective renewable energy sources (RES) and energy storage systems (ESS), and the converters would be controlled independently. However, the multistage configuration generally leads to a large size due to the large number of conversion stages, relatively high cost, and low efficiency and power density. Also, the independent control of several converters and communication among the sources make the system complex. In order to overcome these disadvantages, multi-port DC/DC converters (MPDC) have been proposed. MPDCs are preferred against several independent converters in terms of efficiency, component count, size, cost, and performance point of view. In addition to RES, MPDCs can be utilized in other applications such as electric/hybrid vehicles, telecommunication and satellites, and UPSs. This paper aims to consider the recent advances in MPDC from a topology and control point of view and provide a helpful framework and point of reference for future converter design and applications.

Data exchange among nodes in a distributed dc microgrid (DCMG) causes time delays that can negatively impact reliability and performance. Previous literature often assumes that local data are delayed by the same value as the transmission delay between neighboring nodes, aiming to achieve convergence of average bus voltages to the desired level. However, this assumption relies on having precise knowledge of the communication delay, which is not always feasible in real-world applications. This article presents a more realistic scenario by considering unknown and varying communication delays among links. The assumption of no self-delay for local data results in a steady-state deviation of the global average bus voltages. To address this challenge, a novel observer for average bus voltage is proposed, which significantly expands the acceptable delay range and reduces the communication burden by transmitting fewer variables through the communication links. Furthermore, a modified distributed secondary control scheme is developed, and the system model is transformed into a standard linear form represented by retarded differential equations. Stability analysis and the design of control gains for the system, considering uncertain local and public loads, are presented using the Lyapunov–Krasovskii approach. The proposed method is verified through theoretical analysis, simulation, and experimental results.

Due to the impacts of high intermittent renewable resources, increasing their penetration in the generation sector of energy systems is still challenging. In this regard, the integration of different energy networks can play a key role in dealing with this challenge. This paper focuses on the analysis and optimization of multi-generation energy storage (MGES) system’s performance and investigates the role of this type of energy storage in the operation of future smart energy systems by considering 100% green energy goals. Hence, this paper first introduces high-temperature heat and power storage (HTHPS) system, as a novel MGES unit, for a local integrated energy system (IES) with different energy carriers. Then, a novel optimal energy scheduling scheme for this system is presented by considering the energy hub concept. The proposed IES is introduced as a Smart Energy Hub (SEH) which supplies local energy demands through local renewable resources generation, as well as upstream energy networks, by considering a competitive energy market. Finally, the performance of the proposed SEH is investigated by simulating different case studies and its effectiveness is proved in increasing the renewable generation penetration.

Cascaded configuration of source- and load-side subsystems is a prominent connection form in multiconverter-based low-voltage power distribution networks (e.g., dc microgrids). Despite instability arising from interactions between the individually designed feedback-controlled converters, supplying active loads that act in a tightly regulated fashion, such as constant power loads (CPLs), can yield system instability. In this work, a new source-side active stabilizing scheme is presented based on positive proportional–derivative feedback of the equivalent load current with an intrinsic self-tuning control parameter. It introduces an adaptive-parallel-virtual-resistance (APVR) strategy without affecting the dynamic performance of the load converter. Using this precise control approach that benefits simple structure in design with straightforward control parameter adjustment, the system stability is ensured by actively suppressing CPL destabilizing effect. Moreover, the high robustness and desirable dynamic performance of the APVR strategy are authenticated by considering the plug-and-play of CPLs and unforeseen variations in input voltage amplitude without knowledge of their value. The operational principles and control concepts of the suggested active stabilizer for the three basic dc/dc converters feeding CPLs in cascaded structures are discussed analytically. The effectiveness and flexibility of the APVR method for these systems have been validated using the simulation and experimental results.

By increasing the penetration of wind power in the modern power systems, to investigate transient stability is of special importance. This article presents an innovative index based on the concept of the potential energy boundary surface along with kinetic energy, which aims to detect the transient instability of a power system comprising doubly fed induction generator (DFIG)-based wind farms. Accordingly, transient instability detection (TID) is performed without directly calculating the unstable equilibrium point and thus the computational load is decreased. Since the proposed approach requires only the postfault data that can be easily measured by the phasor measurement units, it is suitable for real-time applications. Therefore, the proposed approach can be applied as a general tool to any power system with any change in topology and operating conditions. Moreover, considering that the current-balance form is the preferred industry model for the implementation of transient stability simulation, the network equations in the current-balance form are extracted for grid-connected DFIG and synchronous generators. Different scenarios are simulated in the Western System Coordinating Council 3-machine, 9-bus system, and the 10-generator New England system. To validate the new index for TID, simulation results are compared with the transient stability index and out-of-step distance relay. The obtained results validate the correctness and effectiveness of the presented new index.

Accurate locating of the faulty section is desired in dc microgrid due to the presence of power electronic converters and low-impedance cables. Some of the existing schemes consider power sources at only one end of the line; thus, assume that the fault current is injected from only one end of the line. This assumption is not true in the case of meshed dc microgrids, where fault current would be supplied from both ends. Moreover, existing communication-based methods require either a fast communication network or data synchronization. To address the aforementioned issues, this article proposes a novel local fault location scheme for meshed dc microgrids. Low- and high-impedance faults are located by measuring the current by localized intelligent electronic device. Based on the parameter estimation approach, the fault location is estimated by sampling the peak values of the fault current. The effectiveness of the proposed strategy is evaluated based on offline digital time-domain simulations in MATLAB/Simulink software environment for a meshed test microgrid system and experimentally verified by implementing in a laboratory-scale hardware setup. Comparing the proposed method with other existing methods proves the effectiveness of the proposed technique for different types of faults.

This article proposes a localized protection scheme for dc microgrids with radial configuration under the impact of constant power loads (CPLs) to determine the location of faults accurately. The proposed fault location scheme is primarily designed for fault location of CPLs in dc microgrids. First, a local protection relay for CPL is designed based on the transient behavior of the current and voltage in the main distribution line. Then, the estimation of the fault resistance is formulated based on the power sharing in the system to improve the accuracy of the protection system. To realize a robust protection scheme considering the variation of fault resistance, a fault resistance estimation procedure is employed to design a system that locates both low- and high-impedance faults. Finally, the effectiveness of the proposed strategy is evaluated based on offline digital time-domain simulations in Digsilent PowerFactory software environment and experimentally verified by implementing on a laboratory scale hardware setup. The obtained simulation and experimental test results, and comparison with other methods prove that the proposed scheme is immune against these disturbances and can efficiently and reliably estimate the location and resistance of faults with high accuracy and acceptable error margin.

This paper addresses the designing of an adaptive type-2 fuzzy PID (T2FPID) controller for load frequency control (LFC) of an interconnected nonlinear power system considering input time-delays. The input delay, which can commonly be raised by failure in the communication links and actuator operating lag may lead to control system instability. In the proposed adaptive T2FPID controller, output scaling factors have been chosen judiciously (according to a stable tuning algorithm) and thus improves the stability and performance of the controlled system. To perform this, the stability of the proposed method has been examined using the Lyapunov–Krasovskii (L-K) theorem, and the adaptation laws of the output scaling factors are derived. The proposed adaptation laws for the output scaling factors are simple and need a little knowledge about the structure of the power system. To demonstrate the efficiency of the proposed adaptive T2FPID controller, a comparison to the non-adaptive T2FPID and type-1 FPID (T1FPID) controllers is given for a two-area interconnected nonlinear power system with input time-delays. The obtained simulation results prove that the performance of the proposed T2FPID controller is superior compared to the other controllers in the presence of time-varying input delays, nonlinearities, and uncertainties.

Purpose: In this paper, a novel Lyapunov–Krasovskii stable fuzzy proportional-integral-derivative (PID) (FPID) controller is introduced for load frequency control of a time-delayed micro-grid (MG) system that benefits from a fuel cell unit, wind turbine generator and plug-in electric vehicles. Design/methodology/approach: Using the Lyapunov–Krasovskii theorem, the adaptation laws for the consequent parameters and output scaling factors of the FPID controller are developed in such a way that an upper limit (the maximum permissible value) for time delay is introduced for the stability of the closed-loop MG system. In this way, there is a stable FPID controller, the adaptive parameters of which are bounded. In the obtained adaptation laws and the way of stability analyses, there is no need to approximate the nonlinear model of the controlled system, which makes the implementation process of the proposed adaptive FPID controller much simpler. Findings: It has been shown that for a different amount of time delay and intermittent resources/loads, the proposed adaptive FPID controller is able to enforce the frequency deviations to zero with better performance and a less amount of energy. In the proposed FPID controller, the increase in the amount of time delay leads to a small increase in the amount of overshoot/undershoot and settling time values, which indicate that the proposed controller is robust to the time delay changes. Originality/value: Although the designed FPID controllers in the literature are very efficient in being applied to the uncertain and nonlinear systems, they suffer from stability problems. In this paper, the stability of the FPID controller has been examined in applying to the frequency control of a nonlinear input-delayed MG system. Based on the Lyapunov–Krasovskii theorem and using rigorous mathematical analyses, the stability conditions and the adaptation laws for the parameters of the FPID controller have been obtained in the presence of input delay and nonlinearities of the MG system. [ABSTRACT FROM AUTHOR]

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Inter-Turn Short-Circuit (ITSC) of the stator winding is one of the most common faults in asynchronous generators. A significant feature of ITSC is the increase of the current in the faulty phase. Improper treatment may lead to unnecessary power loss or further deterioration. Therefore, this paper proposes a fault ride-through strategy under the stator ITSC fault for Doubly-Fed Induction Generator (DFIG) wind turbines. When the closed-loop state observer detects the fault and the current is higher than the rated current, the faulty wind turbine switches to down-regulation mode for protecting the faulty generator. The rotational speed reference is kept at the maximum value. Then the difference between the current and the rated current with the proportion-integration operation is superimposed to the original generator torque reference. Simulation results show that the faulty phase current can be decreased to the rated value, effectively. Although the power output is reduced as well, the impact of the fault does not develop to a failure. So the faulty wind turbine can continue to operate before the maintenance. The proposed strategy can avoid the unnecessary power loss caused by shut-down, improve the operational capacity of wind turbines and reduce the maintenance costs under the ITSC fault.

•A reliability-oriented planning approach is proposed for interconnected energy hubs,•An effective mixed-integer linear programming model is formulated,•Demand response participation is investigated,•The proposed approach promotes renewable resources utilization,•The planned reliable microgrid manifests a profitable grid exchange behavior.

The objective of this paper is to design decentralised sliding mode controllers for fractional-order large-scale nonlinear systems. In the first step, a fully-decentralised fractional-order sliding mode controller with a novel integral sliding manifold is developed. Practical stability of the closed-loop system is fulfilled under the assumption that the interconnections among the subsystems are bounded with known upper bounds. However, in reality the uncertainties and interconnections upper bounds are unknown. Therefore in the next step, an adaptive-fuzzy structure is applied to approximate the interactions and uncertainties. Since the states of neighbour subsystems are considered as the fuzzy system inputs, this technique is known as semi-decentralised control strategy. Due to using the fractional integral sliding surface, the zero convergence of the sliding manifold has been analysed based on integer-order stability theorems. In addition, system tracking errors convergence is deduced from fractional-order linear stability theorems. Computer simulations present the performance of the suggested controllers in the presence of uncertainties and interconnections.

This paper presents some novel fractional-order nonlinear sliding mode controllers for maximum power extraction of a grid-connected wind energy conversion system. Two similar fractional-order controllers with nonlinear sliding manifolds are proposed for generator-side and grid-side converters. The main role of the generator-side controller is regulating the mechanical speed of wind turbine to follow an optimum speed. On the other hand, the grid-side controller main goal is governing the active and reactive power by tuning DC-link voltage. Practical stability of both controllers is achieved by fractional-order nonlinear stability theorems. Comparative simulations are presented to show the effectiveness of the proposed controllers.

This paper presents a control strategy of a hybrid fuel cell/battery distributed generation (HDG) system in distribution systems. The overall structure of the HDG system is given, dynamic models for the solid oxide fuel cell (SOFC) power plant, battery bank and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units and fuel cell to control the power flow from the hybrid power plant to the utility grid are presented. To distribute the power between the fuel cell power plant and the battery energy storage, a neuro-fuzzy controller has been developed. Also, for controlling the active and reactive power independently in distribution systems, the current control strategy based on two fuzzy logic controllers has been presented. A Matlab/Simulink simulation model is developed for the HDG system by combining the individual component models and their controllers. Simulation results show the overall system performance including load-following and power management of the HDG system.

This paper describes a novel strategy developed for optimising the energy flow in a combined hybrid electric vehicle (CHEV) structure. This method implemented an online energy management by a hierarchical hybrid controller between dual sources in this kind of hybrid systems. This structure included two energy sources, the battery and the stack of fuel cells, and its power train system is based on an electric motor (EM) and internal combustion engine (ICE) in a parallel combination. The proposed control method involves a supervisory controller which in the first layer captures all the possible operation modes. In the second layer, an advanced fuzzy hybrid controller has been developed for each of the defined modes. Finally in the third layer of controller, there are local controllers to regulate the set points of each subsystem to reach the best performance and acceptable operation indexes. The simulation results confirm the feasibility and encourage more research toward an actual application.

•This paper proposes a novel controller for a cooling system in smart grid settings and high shares of renewables.•The controller works from a local control entity by responding to a combination of internal and external signals.•Managing the cooling system simultaneously increases the reliability of the microgrid.•The results support that the proposed cooling system controller is capable of planning a microgrid system.