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With the significant trend towards variable frequency in heating ventilating and air-conditioner (HVAC) loads, the inverter-based air conditioner load (IACL) clusters are poised to become the mainstay in participating in demand response (DR). During the process of DR, once the indoor temperature exceeds the comfort constraint, HVAC load must be forced to exit DR, which brings correlation to the behaviour of the preceding and following periods, making cluster optimization modelling and solution difficult. In order to solve the problems, this paper proposes an analogue ON/OFF state-switching (AOSS) control method suitable for IACL cluster participating in DR. Firstly, the critical working point corresponding to the comfort constraint is analysed for eliminating the temporal coupling for IACL. Then, an AOSS control method is proposed based on the critical point analysis. The feasibility of the proposed AOSS control is validated by the experimental results, with the Hisense KFR-75W/T08SBp-A2 inverter-based air conditioning DR experimental platform. Furthermore, by using the proposed AOSS control, a day-ahead scheduling model is constructed, and, the traditional state-queuing (SQ) model is transplanted to the IACL cluster for short-term power control. And the case studies verified the effectiveness and applicability of the day-ahead scheduling model and the transplanted SQ model. • Analysing the critical working point corresponding to the comfort constraint. • AOSS control is proposed to eliminate the temporal coupling for IACL. • Aggregation and optimal dispatching for IACL cluster in day-ahead time scale. • Ultra-short time scale IACL cluster power control. [ABSTRACT FROM AUTHOR]

In the current paper, an improved control strategy designed for synchronizing and transferring autonomous microgrids (MGs) to the grid is presented. The proposed approach is based on an MG leading inverter (MGLI) supplied by a supercapacitor energy storage system, which takes over the MG only during a transitory load and distributes it to the available MG supporting inverters (MGSIs). This paper presents the control systems for both the proposed MGLI and the associated MGSIs, the focus being on the specific issues related to MG synchronization and grid transfer. By means of the proposed solution, the operation of the MG and its transition between autonomous and grid-connected modes require merely the adaptation of the MGLI control system, while the MGSIs operation remain unchanged during all MG states. The comprehensive experimental results, which were carried out on a laboratory-scale MG, have shown that the system is kept stable and with minimum disturbance to the local MG voltage and frequency during the analysed events, namely the scheduled MG transfer to the grid, power-flow control during grid-connection operation, and disconnection from the grid, respectively. [ABSTRACT FROM AUTHOR]

As a main driving force of electric vehicles (EVs), the losses of in-wheel permanent-magnet synchronous motor (PMSM) direct drive system can seriously affect the energy consumption of EVs. This paper proposes a loss optimization control strategy for in-wheel PMSM direct drive system of EVs which optimizes the losses of both the PMSM and the inverter. The proposed method adjusts the copper losses and iron losses by identifying the optimal flux-weakening current, which results in the PMSM achieving the lower losses in the whole operational range. Moreover there are strongly nonlinear characteristics for the power devices, this paper creates a nonlinear loss model for three-phase half-bridge inverters to obtain accurate inverter losses under space vector pulse width modulation (SVPWM). Based on the inverter loss model and double Fourier integral analysis theory, the PWM frequency is optimized by the control strategy in order to maximize the inverter efficiency without affecting the operational stability of the drive. The proposed loss optimization control strategy can quickly find the optimum flux-weakening current and PWM frequency, and as a result, significantly broaden the high efficiency area of the PMSM direct drive system. The effects of the aforementioned strategy are verified by both theoretical analysis and experimental results. [ABSTRACT FROM AUTHOR]

• Study of microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV system. • Development of energy management system based on model predictive control (MPC-EMS). • Results compared with proportional sharing algorithm based on SOC level (SOC-EMS). • Best results obtained from MPC-EMS. This paper presents a new energy management system (EMS) based on model predictive control (MPC) for a microgrid with solar photovoltaic (PV) power plants and a quasi-Z-source cascaded H-bridge multilevel inverter that integrates an energy storage system (ES-qZS-CHBMLI). The system comprises three modules, each with a PV power plant, quasi-impedance network, battery energy storage system (BESS), and voltage source inverter (VSI). Traditional EMS methods focus on distributing the power among the BESSs to balance their state of charge (SOC), operating in charging or discharging mode. The proposed MPC-EMS carries out a multi-objective control for an ES-qZS-CHBMLI topology, which allows an optimized BESS power distribution while meeting the system operator requirements. It prioritizes the charge of the BESS with the lowest SOC and the discharge of the BESS with the highest SOC. Thus, both modes can coexist simultaneously, while ensuring decoupled power control. The MPC-EMS proposed herein is compared with a proportional sharing algorithm based on SOC (SOC-EMS) that pursues the same objectives. The simulation results show an improvement in the control of the power delivered to the grid. The Integral Time Absolute Error, ITAE, achieved with the MPC-EMS for the active and reactive power is 20 % and 4 %, respectively, lower than that obtained with the SOC-EMS. A 1,3 % higher charge for the BESS with the lowest SOC is also registered. Furthermore, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is implemented to validate the simulation results. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the modeling and control of a push–pull converter integrated into a two-stage photovoltaic microinverter operating in island mode without backup energy storage components (batteries). A push–pull small signal model is presented, from which they are derived all transfer functions needed to implement the controllers that regulate the output current, input voltage and output voltage interacting with the MPPT algorithm. A significant contribution of the paper is the proposal of an innovative control structure that simultaneously regulates in island mode both the ac voltage and the dc voltage of the panels, in order to place it in the best operation point. Such operation point is calculated by a specific control loop that interacts with the MPPT algorithm. To validate the proposed concept, simulations in PSIM™ were carried out. [Copyright &y& Elsevier]

Graphical abstract Highlights • Coordinated control of three- and arbitrarily connected single-phase energy sources. • Accurate power flow regulation at the microgrid's point-of-common-coupling. • Unbalance compensation by single- and three-phase inverter-interfaced resources. • Active and reactive power sharing proportional to local power availabilities. • Compliance with constraints and limits of distributed energy resources. Abstract This paper proposes the third generation of the Power-Based Control, that is, an approach to effectively coordinate the operation of single- and three-phase inverter-interfaced distributed energy resources that can be arbitrarily connected among the phases of three-phase four-wire low-voltage microgrids. The aim of the approach is to precisely regulate the power exchanged with the main grid by fairly exploiting the available distributed resources while respecting their own local constraints. This allows to achieve demand-response, unbalance compensation, and improved voltage profiles, which is valuable for limiting stress conditions to the distribution infrastructure. The technique is based on a master/slave microgrid architecture where the distributed inverters act as slave units driven by a centralized master controller. This latter employs the Power-Based Control in order to steer the contribution of the inverters on the basis of the microgrid power status. In particular, active, reactive, and unbalance power terms are processed by the master controller and the corresponding microgrid's power needs shared among the distributed energy resources, to achieve the compensation target at the point-of-common-coupling with the main grid. The strategy proposed herein drives the three-phase inverters to operate balanced, which avoids unwanted voltage fluctuations at the DC-side of the inverters; instead, single-phase inverters, which can be connected arbitrarily among the phases of the distribution grid, are exploited to compensate any residual unbalances (i.e., negative- and zero-components). The control technique is analyzed and demonstrated by computer simulations considering a real urban meshed distribution network. Steady-state and dynamic results and performances are reported and discussed considering typical demand and generation profiles. [ABSTRACT FROM AUTHOR]

This paper presents the design of a discrete-time control scheme for the current injected into the grid by a single-phase voltage source inverter (VSI). The VSI is connected to the grid by means of an LCL filter that attenuates the switching harmonics present in the output waveform of the inverter. The current control is based on a resonant regulator implemented in a Two-Degrees-Of-Freedom (2DOF) scheme that allows the location of all the poles to be defined in the closed loop of the system without the need for observers and measuring only the current injected into the grid. This control scheme, therefore, allows the attenuation of the resonance frequency of the LCL filter and requires no additional damping methods with which to mitigate the resonance phenomenon. The design parameters can be obtained using a fairly straightforward mathematical approach that involves only operations with real numbers. The simulation and experimental results obtained show that the control scheme performs correctly even considering changes in the grid inductance. • The current control for a single-phase inverter with an LCL filter is addressed. • A fast response and zero-tracking error is achieved. • The design methodology permits the complete definition of the closed-loop poles. • Only the grid-side current is needed for control and damping purposes. • The control stability against changes in the grid inductance is addressed. [ABSTRACT FROM AUTHOR]

The rapid developments of advanced metering infrastructure and dynamic electricity pricing provide great opportunities for residential electrical appliances, especially air conditioners (ACs), to participate in demand response (DR) programs to reduce peak power consumptions and electricity bills. One of the biggest challenges faced by residential DR participants is the lack of intelligent DR control methods which enable residential ACs to automatically respond to dynamic electricity prices. Most existing studies on DR control of residential ACs focus on single-speed ACs. However, inverter ACs which have higher part-load efficiencies have been extensively installed in today’s residential buildings. This paper presents a novel model-based DR control method for residential inverter ACs to automatically and optimally respond to day-ahead electricity prices. A control-oriented room thermal model and steady-state model of inverter ACs are developed and integrated to predict the coupled thermal response of the room and AC for the purpose of model-based control. Optimal scheduling of indoor air temperature set-points is formulated as a nonlinear programming problem which seeks the preferred trade-offs among electricity costs, thermal comfort and peak power reductions. Genetic algorithm (GA) is used to search the optimal solution of the nonlinear programming problem. Simulation results show that compared with the baseline case, the proposed model-based optimal control method can reduce the whole electricity costs and the peak power demands during DR hours while meeting thermal comfort constraints. Besides, sensitivity analyses on the trade-off weightings in the optimization objective function demonstrate that electricity costs, occupant comfort and peak power reductions are sensitive to the weightings and the use of the weightings is effective in achieving the best trade-off. [ABSTRACT FROM AUTHOR]

The effective design of Distributed Energy Systems (DES) is subject to multiple uncertainties related to aspects like the availability of renewable energy, the building energy demands, and the energy carrier prices. Nevertheless, current practices involve the use of deterministic design models, which overlook uncertainty and can lead to suboptimal DES configurations that fail to deliver the desired performance. A necessary condition in order to obtain robust DES designs against uncertainty is the understanding of uncertainty’s impacts and main drivers. Therefore, this paper presents a novel methodological framework for the investigation of uncertainty in the context of DES design, which combines optimisation-based DES models and techniques from Uncertainty Analysis (UA) and Global Sensitivity Analysis (GSA). Moreover, the application of the framework is illustrated with a case study for the optimal DES design of a Swiss urban neighbourhood. Embarking from a deterministic DES design model, first, all sources of uncertainty are identified and appropriate probabilistic descriptions are assigned to all uncertain model parameters. UA is then performed using Monte Carlo (MC) simulations to quantify the impacts of uncertainty. Results reveal substantial variations in terms of economic and carbon performance of the optimal DES, but also in terms of optimal DES configurations. Moreover, the UA results indicate that the optimal system costs are mostly higher than the deterministic cost estimates, while the inverse is observed for the case of carbon emissions. Additionally, in many of the MC simulations, the resulting optimal DES configurations deviate significantly from the deterministically obtained designs, which confirms the risk of suboptimal decisions in deterministic design processes. Moreover, the results of UA can function as decision support by identifying the DES configurations that are optimal for most realisations of uncertainty. Finally, to identify the uncertain parameters that are mostly responsible for the variation of the economic performance of the DES, a two-step GSA is launched, combining the Morris method and the variance-based Sobol method. Results of the GSA indicate the energy demand patterns and the energy carrier prices as primarily responsible for the variability of the optimal system cost, while parameters like the investment costs and the technical characteristics of the technologies exert only minimal influence. The results of GSA, besides offering a better understanding of uncertainty to DES designers, also identify the parameters for which additional effort needs to be invested to reduce their uncertainty and, as a result, the uncertainty associated with DES design. [ABSTRACT FROM AUTHOR]

The large-scale application of renewable energy is promising to solve the energy crisis over the world. Renewable energy is generally integrated into distribution networks or microgrids through inverters. Inverter-interfaced distributed generators (IIDGs) have the advantage of utilizing renewable energy effectively and flexibly. However, the wide interconnection of IIDGs causes transient stability to the public grid. This paper presents the transient stability mechanism of the grid-connected IIDGs using droop control. The transient stability mechanism is obtained by combining the transient stability condition and the comprehensive dynamic trace. The transient stability condition is proposed by the transient model and IIDGs’ operation features. The comprehensive dynamic trace is formulated by the active and reactive power curves during transient events. The mechanism is able to reflect the relations between transient stability and droop factors and reveal the transient behaviors of IIDGs. The transient stability judgment is correspondingly developed. A series of simulations demonstrate the correctness and effectiveness of the transient stability mechanism. The transient stability mechanism better expands and develops the utilization of renewable energy. [ABSTRACT FROM AUTHOR]

According to the recently proposed concept of PV-STATCOM that utilizes photovoltaic (PV) inverter as STATCOM, PV solar farm plays an increasingly important role in providing fast reactive power compensation, especially during the voltage recovery processes under voltage sag or post-fault conditions. To relieve the enormous economic losses caused by the inefficiency in voltage recovery scenario, the reactive power fast response characteristic of PV should be adequately considered in optimal siting and sizing of distributed generation. In this paper, a weighted voltage support ability index (WVSAI) based on sensitivity analysis has been firstly used to quantify the influence of PV-STATCOM on voltage recovery efficiency under voltage sag or post-fault conditions. With the WVSAI added to traditional distributed generator (DG) planning constraints, a modified optimal siting and sizing model is proposed for the targets of minimizing the total annual cost associated with the DGs to be planned. The proposed model is classified into the type of mixed integer nonlinear programming (MINLP) and then relaxed by second order cone programming (SOCP). After relaxation, commercial solver CPLEX through YALMIP platform is used to solve the relaxed model. The proposed model has been applied in IEEE 33-bus distribution system under scenarios with different WVSAI restrictions. Based on the optimal solutions of DGs’ siting and sizing, PSCAD simulation tool is used to emulate voltage recovery processes of a specific sensitive load under voltage sag, and thus demonstrates the feasibility and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

• Frequency-watt, volt-watt, and power curtailment methods were analyzed using smart PV inverters. • Power curtailments were discussed at low and high PV penetration areas. • Effects on the distribution voltage are described at the service transformer level. • Control performances were evaluated. • Experimental analyses were performed at the Maui Smart Grid project, Hawaii. Large-scale deployments of variable renewable energy sources, such as photovoltaic (PV) systems, are increasing around the world. PV systems are a potential source of clean energy but they experience power intermittency and lack controllability. However, smart PV inverters provide grid-friendly functionalities that control the power output of PV systems. Power intermittency of PV systems causes major problems such as voltage fluctuations and frequency deviations in an electric power grid. Together with varying loads and other renewable distributed generations, the grid frequency and voltage become difficult to manage. A smart PV inverter allows for active power curtailment, volt-watt, and frequency-watt control systems to mitigate the voltage and frequency deviations for a smart power grid. Therefore, smart PV inverters can reduce the installation of voltage and frequency control devices in an electric power grid, which in turn can reduce installation and maintenance costs. Real-time analyses of active power curtailment, volt-watt control, frequency-watt control using smart PV inverters and their effects on voltage and frequency are presented in this paper. Power curtailment operations were executed in low and high PV penetration areas. From the experimental analyses, distributed voltage deviations can be mitigated using active power curtailment and volt-watt control systems, and the over-frequency of an electric power grid can be reduced using frequency-watt control method. Controller performances of smart PV inverters are also evaluated in this paper. The experimental analyses were executed in the Maui Advanced Solar Initiative Project. [ABSTRACT FROM AUTHOR]

Abstract: The increasing use of small wind energy has made it necessary to develop new methods to improve the efficiency of this technology. This improvement is best achieved considering the interaction between the various components, such as the wind rotors, the electrical generators, the rectifiers and the inverters, as opposed to studying the individual components in isolation. This paper describes a methodology to increase the efficiency of Small Wind Turbines (SWTs) equipped with a Permanent Magnet Synchronous Machine (PMSM). To achieve this objective, capacitor banks will be connected between the PMSM and the rectifier. This methodology is motivated by two clear aims. The first one is to operate the SWT with its maximum power coefficient C p . The second one is to select the most suitable capacitor bank for each wind speed to optimise the energy supplied to the grid. The methodology will be tested on a commercial 3.5kW SWT, and the results will be studied to determine its feasibility. [Copyright &y& Elsevier]

Abstract: In this paper is proposed a nonlinear current-mode control for the fuel cell/battery/ultracapacitor hybrid power sources (HPS) that improves the ripple factor of the fuel cell current. The nonlinear current control is analyzed and designed using a systematic approach. The design goal is to generate an anti-ripple via buck current controlled source in order to mitigate the inverter current ripple. All the results have been validated in several simulations. The simulation results successfully show that nonlinear current-mode control determines in the low frequency-domain better performances than other current-mode control techniques, such as the hysteretic current-mode controller or the peak current-mode controller. The current ripple factor is one of the used performance indicators. [Copyright &y& Elsevier]

Abstract: This paper presents the analysis and comparison of the main active techniques for islanding detection used in grid-connected microinverters for power processing of renewable energy sources. These techniques can be classified into two classes: techniques introducing positive feedback in the control of the inverter and techniques based on harmonics injection. Accurate PSIMTM simulations have been carried out in order to perform a comparative analysis of the techniques under study and to establish their advantages and disadvantages according to IEEE standards. [ABSTRACT FROM AUTHOR]

This paper describes a numerical approach to power-loss minimization in a fractional hp induction motor driven by a voltage-source inverter. The motor parameters are obtained from a genetic algorithm search. Optimum voltage and frequency excitations are arranged as a table for an energy-saving controller. The proposed method is useful under variable-torque load conditions. Simulation and experimental results are presented. [Copyright &y& Elsevier]

• Integrated design of heat sink considering the layout of power devices was performed. • Temperature distribution and fluid velocity filed of three heat sinks were analyzed. • Effects of fin thickness and flow rate on temperature and pressure drop was studied. • The accuracy of the numerical simulation results has been verified by the experiment. • The motor inverter with the new configuration heat sink achieves high power density. The rapid development of power electronic devices has made them have higher power density, which puts forward higher requirements for cooling technology. The contribution of this paper is the integrated design of the liquid cooled heat sink for a 30 kW motor inverter considering the distribution of power devices. In order to find an optimal heat sink configuration, the cooling performance of three different configurations of heat sinks was investigated. And the distribution characteristics of the temperature and fluid velocity field were compared and analyzed. The heat sink with serpentine channel configuration was selected due to its best temperature uniformity and cooling characteristic. In addition, the effects of geometric parameters (fin thickness) and flow parameters (flow rate) on cooling performance were further studied. On this basis, the geometrical configuration of the heat sink was optimized. The experimental results of the optimized heat sink are in good agreement with the numerical simulation results. The motor inverter achieves high power density of 9.677 kW/kg. [ABSTRACT FROM AUTHOR]

• A comprehensive optimal coordination model of VPP and a novel distributed online algorithm are proposed. • The presented method significantly reduces the computational and communication complexity. • The VPP operator can generate the inventive signals based on privacy-protected measurement feedback. • Each device uses a closed-form strategy to update its setpoint locally based on currently observable information. • The optimality of the proposed algorithm is characterized and guaranteed mathematically. This paper presents a temporally coupled distributed online (TDO) algorithm to aggregate and coordinate numerous networked distributed energy resources (DERs) as a virtual power plant (VPP). A centralized stochastic optimization problem is formulated to minimize the long-term social utility loss while satisfying the voltage security, operational requirements of DERs, and VPP service requests. After that, we propose the TDO algorithm to reformulate the primary problem as an adaptation of online convex optimization (OCO). In particular, the temporally coupled constraints are well separated to each timeslot. In real-time operation, the VPP operator updates the incentives according to the measurement feedback. The smart energy gateways (SEGs) equipped at each node maximize their income and utility based on the received incentive signals through adjusting the setpoints of the governed photovoltaics (PV) inverters and electric vehicles (EVs). Unlike conventional distributed optimization algorithms where complicated iterative procedures between agents are unavoidable, the proposed TDO algorithm is computation- and communication-efficient since the SEG can directly employ the closed-form optimal setpoints without iterative communications once receiving the incentives. Furthermore, we design an incentive scheme to coordinate the SEGs based on the privacy protected nonintrusive measurements instead of direct control. Optimality and convergency of TDO are analyzed mathematically. Finally, the proposed method is corroborated numerically on a modified 33-node test feeder. A larger system is tested to validate the computational time performance. [ABSTRACT FROM AUTHOR]