Search

This paper proposes a tube model predictive control method considering uncertainties of renewable energy generation in the low-voltage distribution network. For relatively low dependence on communication networks, a decentralized voltage control framework is urgently needed to be developed for voltage regulation in the low-voltage distribution network. Opposed to the traditional voltage control techniques, a novel decentralized tube model predictive voltage control (TMPC) strategy is proposed. First, this strategy entails the formulation of a discrete model encompassing distributed photovoltaic units and energy storage systems intertwined with the distribution grid model based on voltage sensitivity. Then, considering the worst case of voltage deviations caused by uncertain and stochastic power fluctuation, we specifically discuss a robust positively invariant to determine the control section of controllers. Further, the strategy employs tube model predictive controllers encompassing nominal and auxiliary controllers in distribution areas. The nominal controller generates a central path for different voltage operating points of each distribution area, and the auxiliary controller makes all trajectories lie in a bounded neighborhood called a tube. The effectiveness of the proposed control strategy is investigated on a test system containing renewable energy resources. • A novel decentralized control structure is proposed to serve voltage control for distribution networks, which can cooperate for accurate voltage control with random and fluctuant renewable energy. • In the nominal controller, operation points of DGs are generated considering the generation and load scheduling. In the auxiliary controller, detailed control objectives and constraints are proposed for suppressing disturbances of DGs. • To balance the conservation and performance, a worst-case-based robust positively invariant is developed to quantify the range of tubes to cope with the randomness. [ABSTRACT FROM AUTHOR]

This paper proposes a novel inertia-enhanced distributed control method to complement the inertia of microgrids. The rate of change of frequency (RoCoF) and the rate of change of voltage (RoCoV) are employed in this paper to quantify the frequency inertia and voltage inertia, respectively. Then, a fully distributed algorithm with constrained changing rates is proposed. By bounding the changing rates of frequency and voltage during the consensus control, the algorithm can address the consensus problem while enhancing the inertia of microgrids. Compared with most inertia control methods, the proposed method can utilize the reserve power of scattered DGs to supply inertia. Besides, it performs better under disturbances and delays than conventional distributed control methods. The effectiveness of the proposed method is validated by several cases in MATLAB/Simulation and a hardware experiment. [ABSTRACT FROM AUTHOR]

Highlights • The proposed control strategy using PVs to cooperate with NDC unilaterally. It does not change the original control strategy in VQC system, which makes it easy to achieve in the project and reduces project investment. • Voltage feedback is applied in the reference value track to eliminate deviations. • Voltage and reactive power violations can be solved in a timely and economical way compared to the NDC strategy. Abstract The increasing penetration of photovoltaics (PVs) and fluctuating load exacerbate the risk of voltage and reactive power violations in distribution systems. The conventional regulation strategy is based on the nine-zone diagram control (NDC), which is difficult to quick response and meet the requirement with high precision. Utilizing the delay of NDC, a nonintrusive control strategy of voltage and reactive power for distribution systems is developed in this paper. The proposed control strategy uses the ability of PV to cooperate with traditional devices without changing the original NDC strategy, which makes it easy to implement and extend in the project. First, a time-series control architecture is developed to reduce the number of traditional devices and eliminate voltage violations. Then, by using the sensitivity values of multiple devices, the reactive power output of PVs is calculated, and the voltage reference value in PV inverter control (PVC) horizon can be tracked based on feedback. A case study is carried out on an IEEE 33-node system to illustrate the effectiveness of the proposed method. It is shown that PV can be used as a continuous reactive power source to realize fast and accurate regulation and the proposed method can improve adjustment accuracy and reduce the operation of conventional equipment compared to the NDC. [ABSTRACT FROM AUTHOR]

The inverter control plays a critical role in microgrid (MG) hierarchical control structure. In this paper, a dominant dynamic elimination control is studied for the voltage-controlled MG inverter. A compact control structure is designed to include separated static state feedback and feedforward terms. Benefitting from the designed control structure, the dominant dynamic can be canceled by the static feedforward control via the fundamental zero-pole cancelation principle. Thanks to the cancelation of the dominant dynamic, the load disturbance-rejection performance is improved, and the approximate unity gain from the reference to output is also achieved from the perspective of the application control layer, thereby the performance of power control for the upper application is improved. Furthermore, the strong robustness to parameter variations and low total harmonic distortion are also achieved. Comparative simulations and experiments are adopted to verify the effectiveness and superiority of the designed approach. [ABSTRACT FROM PUBLISHER]

An optimal grid current control strategy with grid voltage observer (GVO) for LCL‐filtered grid‐connected inverters is proposed in this paper. The quasi proportional resonant (QPR) controller is applied in this control strategy conducted in a stationary αβ frame to suppress the transient fluctuations and the total harmonic distortion (THD) of the output grid current and achieve faster transient performance. Active damping is chosen as the damping method in this paper, which uses the capacitor current acting as the feedback of the inner current loop to replace the actual resistor in parallel with the filter capacitor digitally. The LCL‐filtered resonance frequency can be changed by this virtual impendence, and the control system will be stabilized more effectively. In this proposed control strategy, a GVO is introduced to replace the actual sensors, the sampling precision of which can be influenced negatively in the actual experimental environment. The introduced GVO can provide clean and noise‐free estimation of the grid voltage and also reduce the overall cost of the whole control system. The estimated grid voltage acts as the feedforward of the internal current loop, which accelerates the regulating rate of the internal current loop, improves the dynamic response of the system effectively, and restrains the influence caused by grid voltage variation. Finally, the validity of the proposed approach is verified through simulations and a three‐phase prototype test system with a TMS320F28335 digital signal processor. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

To improve the control performance for grid-tied power converters, the fundamental frequency and harmonics of the grid voltage should be quickly and accurately estimated even under distorted voltage condition. This paper introduces a straightforward discrete adaptive filter to observe fundamental and harmonic sequence components of the grid voltage. The proposed filter possesses a simple and straightforward implementation. Based on the newly developed filter, frequency error transmission was analyzed when the frequency of the input voltage was unequal to the center frequency of the filter. Consequently, a frequency estimation loop was designed to adapt to the frequency variation for the filter. Compared to previous algorithms, the proposed algorithm has a better dynamic performance rating for frequency estimation, robust stability, and a simpler implementation. The effectiveness of the algorithm is verified by simulations and laboratory experiments. [ABSTRACT FROM PUBLISHER]

This paper proposes an improved continuation power flow (CPF) method for the modelling and stability analysis of distribution systems with a high penetration of distributed generation (DG). This method aims at solving the flaws of conventional CPF in the description of DGs, the allocation of unbalanced power and the consideration of renewables. To indicate the power variations of DGs with respect to terminal voltage and system frequency precisely, the comprehensive static characteristics bus models are introduced into the calculation of the equilibrium point. Then, in the case of multiple generations, the distributed slack bus model based on incremental loss factors (ILFs) is used to allocate unbalanced power, making the results of CPF independent of slack bus selection. In addition, the load growth pattern involving the output characteristics of renewables is reinterpreted as the net load growth pattern to reflect the intermittency and fluctuation of renewables on the static stability of distribution systems. A detailed solution process of improved CPF is then elaborated. Case studies are presented on the IEEE 33-bus distribution system to illustrate the validity of the improved CPF method, and more simulations on the PG&E 69-bus distribution system are performed to assess the effect of DGs on the static stability of distribution systems. [ABSTRACT FROM AUTHOR]

• A novel model for low-voltage distribution areas based on genetic algorithm is developed, which simplifies the complexity of online computation and suppresses the inner voltage deviations in a safe section. • The coordination of PVs and ESs at different voltage levels is promoted to improve the voltage regulation while short of the reactive power capacity of PVs. • A tube-based MPC controller is proposed for voltage fluctuation under uncertainties introduced by power disturbance and a genetic-algorithm-based equivalent model of low-voltage areas, with which a distribution network can work in common conditions under variable operations of PVs. With the ever-growing penetration of distributed generators (DGs), voltage deviation caused by randomness and fluctuation has become increasingly prominent in distribution networks. Conventional voltage control cannot sufficiently utilize the rapid and flexible characteristics of DGs. In this paper, a tube-based model predictive control (TMPC) method is proposed to address voltage violation and fluctuation difficulties considering the uncertainties of renewable energy. Firstly, a simplified model approach based on a genetic algorithm (GA) is proposed to unify numerous DGs in low-voltage distribution areas. Then, based on this simplified model combined with the voltage sensitivity model, the TMPC controller is designed for the whole distribution network, which consists of two subsidiary controllers to suppress voltage deviation caused by uncertainties. The former is used to generate a central path for different operating points of the grid, and the latter is designed to track the path in a bound tube. The proposed method can cope with the uncertainties caused by external disturbances such as drastic power fluctuations. Finally, the numerical simulation in the case studies demonstrates the effectiveness of the proposed method in accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a sinusoidal voltage signals tracking control strategy, adaptive for frequency of a three-phase inverter for a battery energy storage system (BESS) applied to an isolated microgrid. To support the normal operation of distributed renewable energy and feed the critical loads under the isolated mode, the BESS generally works in voltage control mode (VCM). The proposed control strategy, which transforms the tracking control problem into a state feedback control problem, includes two terms, one of which is state feedback control used to stabilize system while another employs multiple resonant controllers applied to achieve harmonics compensation control. The optimal linear-quadratic (LQ) control approach in which the root locus method is used for optimization selection of weight matrix Q is adopted to tune the control parameters of multiple resonant controllers. The proposed control strategy performs outstanding voltage control performance to maintain an excellent voltage level such as zero steady-state error and low total harmonic distortion (THD) under the situation of sudden load changes, back power flow of renewable energy such as photovoltaic and nonlinear load in an isolated microgrid. Finally, the validity of the proposed approach is verified through simulations and a three-phase experiment prototype of BESS with TMS320F28335 DSP. [ABSTRACT FROM AUTHOR]

The increasing penetration of photovoltaic generation exacerbates the risk of voltage violations in distribution networks. One viable tactic for increasing the flexibility of regional distribution networks is to use the thermal inertia of community heating systems (CHSs). However, the slow heat dynamics in the heating network brings difficulties in synchronous joint operation decisions of the integrated system. In this paper, we propose a novel power-to-temperature sensitivity model (PTSM), equating the whole CHS to a flexible electric load with thermodynamic characteristics. It denotes the direct relationship between the average water temperature change and the electric power consumed by ground-source heat pumps (GSHPs). A robust collaborative voltage optimization model is then developed from the perspective of power distribution system operators. The PTSM provides accurate prediction of CHS temperature variations to construct the operation constraints of GSHPs. This mixed integer programming problem is solved by the column-and-constraint generation algorithm. The test results of an actual residential community demonstrate that the PTSM can ensure the prediction errors of the CHS average temperature within ±0.4 °C in case of the optimal time resolution and aggregated heating load location. An IEEE 69-bus distribution network with several CHSs is studied to show that, the flexibility of CHSs can achieve an extra 17.25% reduction of the daily voltage deviation. The proposed method has significant advantages in computation time and robustness. • A whole CHS is equated to a flexible electric load by PTSM for voltage optimization. • PTSM denotes CHS average temperature change, omitting thermodynamics of components. • Robust voltage optimization by CHSs and electrical device coordination is studied. • PTSM is verified by the measured data of actual community heating system. • PTSM-based collaborative method has advantages in computation time and robustness. [ABSTRACT FROM AUTHOR]

To improve the filtering capability of frequency-locked loop (FLL), the high-order bandpass filters FLL was proposed recently. This article proposes a high-order FLL in synchronous (dq) reference frame where the high-order low-pass filter is adopted. A general analytical model is established for the high-order FLL. Based on the model, it is proven that the conventional high-order FLL exhibits no improvement in terms of filtering ability of the frequency estimation. Based on this analysis, a new frequency estimation loop is proposed to obtain an enhanced filtering capability for the FLL. Additionally, the proposed high-order FLL has the advantage of simple implementation compared to conventional high-order FLLs. A design example is then demonstrated and simulated to show the accuracy of the model and the effectiveness of the proposed FLL. Finally, the proposed high-order FLL is experimentally verified on a testbed using a 32-bit floating-point DSP TMS320F28379D at 200 MHz. [ABSTRACT FROM AUTHOR]

This paper proposes a coordinated optimal control strategy of PV generators and air-conditioning loads, in order to handle the possible voltage beyond limit issues resulting from high penetration of PV generators in the distribution networks. This strategy is achieved via coordinately considering the node voltage sensitivity and the adjustment-compensation bid model, to improve the economy of the whole system. As a result, the shortage of the PVs’ reactive power control capability is compensated by the adjustable air-conditioning loads, so that the waste of the photovoltaic power can be reduced or even avoided. The case study using an IEEE standard 33-node system, which is further updated with the installation of 5 PV generators and 5 air-conditioning loads, validates the correctness and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In classical inverter control, load current (disturbance) decoupling control is often used to improve the control performance. Yet, in a recent state-space control structure for multiresonant controllers, the load current decoupling technique is less studied. Moreover, in the classical control, the load current decoupling only has one control degree of freedom. Therefore, in this paper, a load current decoupling control combed linear quadratic (LQ) regulation is investigated, the proposed control structure that manipulates α and β axes as a unified system is adopted to increase the control degree of freedom. The LQ control synthesizes the state feedback control law including gains of the resonant controllers. Two general criteria, namely H\infty norm and zero dynamic, are proposed as the design guideline for the load current decoupling control. The effectiveness and robustness of the proposed approach are validated through MATLAB/Simulink simulations and experiments with a 5-kVA testbed. The results prove that some favorable performances, for example, the fast recovering time, the small voltage drop, and the low total harmonic distortion, are achieved by the proposed approach compared to the classical dual-loop proportional-resonant (PR) control with load current decoupling and the optimal H\infty control. [ABSTRACT FROM AUTHOR]

In this paper, a distributed economic dispatch scheme considering power limit is proposed to minimize the total active power generation cost in a droop-based autonomous direct current (DC) microgrid. The economical dispatch of the microgrid is realized through a fully distributed hierarchical control. In the tertiary level, an incremental cost consensus-based algorithm embedded into the economical regulator is utilized to search for the optimal solution. In the secondary level, the voltage regulator estimating the average voltage of the DC microgrid is used to generate the voltage correction item and eliminate the power and voltage oscillation caused by the deviation between different items. Then, the droop controller in the primary level receives the reference values from the upper level to ensure the output power converging to the optimum while recovering the average voltage of the system. Further, the dynamic model is established and the optimal communication network topology minimizing the impact of time delay on the voltage estimation is given in this paper. Finally, a low-voltage DC microgrid simulation platform containing different types of distributed generators is built, and the effectiveness of the proposed scheme and the performance of the optimal topology are verified. [ABSTRACT FROM AUTHOR]

An enormous challenge for state estimation (SE) in power distribution networks with high penetration of photovoltaic generators lies in how to deal with measurement uncertainty. Driven by this motivation, an interval arithmetic (IA) based SE is proposed in this paper, which considers interval modeling for measurement uncertainty. The proposed SE is formulated as two interval optimization models based on the unknown-but-bounded theory, and solution bounds of state variables are obtained using a two-stage linear programming approach. In particular, the proposed SE is extended to realistic power distribution networks with mixed microphasor measurement units (μPMU), voltage magnitude, smart meters and feeder terminal units. Case studies and results are illustrated and discussed to demonstrate the performance of the proposed IA-based SE. It could provide the operators intuitive and effective bounds of system states for advanced power industrial applications under consideration of uncertainty. [ABSTRACT FROM AUTHOR]

Along with the rapid development of electric vehicle (EV) charging technologies, many new types of charging facilities have been utilized in electric vehicle charging stations (EVCSs). Charging facilities with different rated charging power can satisfy the charging demands from diverse EV owners, and simultaneously impact the spatial and temporal distribution of EV charging demands, which in consequence challenges the rationality and economy of EVCS allocation schemes. Based on this background, this paper indicates that EVCSs should be regarded to comprise multi-types of charging facilities during the planning stage, and a new optimization model is proposed for the target of minimizing the annualized social cost of whole EV charging system. To process the complexity of the optimization model, a two-step equivalence is proposed and applied. After the equivalence and some exact relaxation, the proposed optimization model has been transformed into the type of mixed integer second-order cone programming (MISOCP), which can be efficiently solved by appropriate mathematical methods. To demonstrate the feasibility and effectiveness of the proposed approach, a practical urban area fed by a 31-bus distribution system in China has been used as the test system and the numerical results are presented and analyzed. [ABSTRACT FROM AUTHOR]

Due to the increasing penetration of the uncertain single‐phase distributed generations (DGs), the current distribution networks are becoming more uncertain, unbalanced, and complicated than ever before, which brings great challenges for distribution network operators. This study proposes an adaptive robust optimal reactive power dispatch approach for the unbalanced distribution networks (U‐DNs) considering uncertainty caused by DGs. Leveraging the reactive power compensation from inverters of DGs, the purpose of the proposed method is to minimise power losses and maintain the voltage within regulatory limits. The feasible region of DGs is estimated and considered as a new constraint, aiming to guarantee the reliable operation of U‐DNs. The optimal reactive power dispatch problem is then formulated as an adaptive robust optimisation problem based on semidefinite programming. The adaptive function, which derives the relationship between reactive power and active power outputs of DGs, is utilised to make the method more flexible and less conservative. The cutting plane algorithm is introduced to solve the proposed adaptive robust reactive power dispatch model efficiently. Moreover, case studies are separately conducted on the modified IEEE 13‐bus and 123‐bus test systems to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• A VSG-based hierarchical control scheme is proposed for DGs in active distribution network. • Multiple VSG-based distributed generators can enhance the inertia of system through regulating the equivalent output power. • In order to minimize the voltage deviation and power loss, we adopt model predictive control to cooperate DGs. With the increasing penetration of renewable energy, converters need to help enhance the stability and rigidity of the power system. This paper proposes an inertia-enhanced method with the hierarchical control scheme for active distribution network to support inertia for the utility grid. The paper first analyzes the mechanism and influence of inertia in power systems and quantifies the inertia which an active distribution network can supply. Then, two-layer control structure is designed for favorable control performance. At the primary control layer, a virtual synchronous generator control strategy is adopted for instant inertia support under frequency fluctuation. The objective of primary control is to track the control references rapidly and accurately. At the secondary control layer, the objective is to coordinate the active and reactive power output of distributed generators to keep voltage deviations and power loss of internal distribution network operating at a comparatively appropriate level. The secondary control strategy is based on model predictive control method, which can consider the physical and control constraints of distributed generators and find the optimal reference signals for all the primary controllers to track. The inertia of power system is apparently enhanced with the hierarchical inertia-enhanced scheme. Finally, simulation based on Matlab/Simulink is carried out, and the feasibility and validity of proposed control strategy are verified. [ABSTRACT FROM AUTHOR]

With the increasing penetration of distributed photovoltaics (PVs) in active distribution networks (ADNs), the risk of voltage violations caused by PV uncertainties is significantly exacerbated. Since the conventional voltage regulation strategy is limited by its discrete devices and delay, ADN operators allow PVs to participate in voltage optimization by controlling their power outputs and cooperating with traditional regulation devices. This paper proposes a decoupling rolling multi-period reactive power and voltage optimization strategy considering the strong time coupling between different devices. The mixed-integer voltage optimization model is first decomposed into a long-period master problem for on-load tap changer (OLTC) and multiple short-period subproblems for PV power by Benders decomposition algorithm. Then, based on the high-precision PV and load forecasts, the model predictive control (MPC) method is utilized to modify the independent subproblems into a series of subproblems that roll with the time window, achieving a smooth transition from the current state to the ideal state. The estimated voltage variation in the prediction horizon of MPC is calculated by a simplified discrete equation for OLTC tap and a linearized sensitivity matrix between power and voltage for fast computation. The feasibility of the proposed optimization strategy is demonstrated by performing simulations on a distribution test system. [ABSTRACT FROM AUTHOR]