Abstract:In this paper, a cloud-edge-end collaboration-based control architecture is established for frequency regulation in interconnected power systems (IPS). A model predictive control (MPC)-based load frequency control strategy for the IPS with photovoltaic aggregation and energy storage systems under model uncertainty and communication delay is proposed. This can efectively overcome the issues of model uncertainty, random load perturbation and communication delay. First, a state space model for the IPS is constructed. To coordinate the frequency and contact line power fuctuation of the IPS, a robust controller based on the theory of MPC is then designed. Then, considering the communication delay of frequency response commands during transmission, a predictive compensation mechanism is introduced to eliminate the efect of delay while considering model uncertainty. Finally, simulation results verify the efectiveness and robustness of the proposed control strategy.

Abstract:The automatic reclosing strategy is an efective measure to improve the reliability of a distribution network. It can quickly clear instantaneous faults in the grid. The traditional transformer has proven to be reliable and robust during the reclosing process. However, the infuence of the reclosing process on the operational characteristics and reliability of solid-state transformers (SST) is still unclear. The reclosing action may generate a huge inrush current, resulting in shutdown and even damage of the SST. To address this problem, this paper proposes an inrush current suppression strategy. First, the operational performance of the SST under a reclosing process is discussed, and the inrush current generation mechanism is analyzed in detail. Then, considering the controllability of distributed generation (DG), a novel DG-supported inrush current suppression strategy is proposed. The suppression ability of the DG on inrush current in diferent initial conditions is analyzed. Finally, the efectiveness of the proposed strategy is verifed by simulation and experiment. These show that the proposed strategy can help to enhance the FRT capability of the SST, as well as support the SST to maintain continuous power supply and physical integrity during grid faults.

Abstract:The multi-chip parallel insulated gate bipolar transistor (IGBT) is the core device in large-capacity power electronic equipment, but its operational reliability is of considerable concern to industry. The application of IGBT online degradation state analysis technology can be benefcial to the improvement of system reliability. The failure mechanism of IGBT devices is discussed in this paper, and a technique for analyzing the degradation state of IGBT based on apparent junction temperature is proposed. First, the distortion consistency of the voltage rise time in various failures is discussed, and the junction temperature dependence of the voltage rise time is then demonstrated. Subsequently, an apparent junction temperature model based on the voltage rise time is established (the ftting accuracy is as high as 94.3%). From the high-frequency model in the switching process of the device, an online extraction technology of key parameters (e.g., voltage rise time) is developed. Finally, an experimental platform for IGBT degradation state estimation is established, and the feasibility of IGBT degradation state estimation based on apparent junction temperature is proved, especially the degradation of bonding-wire and the gate-oxide-layer. The experimental results show that the proposed IGBT degradation state estimation technique based on apparent junction temperature is a reliable online estimation method with non-contact, high accuracy, and comprehensiveness.

Abstract:When conducting relay protection research, research costs can be signifcantly reduced if protection principle development, protection parameter verifcation and debugging can be carried out without relying on actual protection devices. The concept of ‘digital twin’ has made this possible, but the existing research has shortcomings in real-time data interaction ability, protection logic transparency, interface standardization, human–computer interaction etc., and consequently,mirror operation of relay protection in digital space has not been fully realized. Therefore, referring to the characteristics of digital twin, and combining with the practical application requirements in relay protection, this paper proposes the concept and characteristics of relay protection mirror operation based on digital twin. Key solutions are proposed to address the difculties that may be encountered in the implementation of relay protection mirror operation in terms of protection principles, interfaces, real-time operation of the system, and human–computer interaction function simulation. Finally, an example of 110 kV double-bus and double-branch bus protection is used to verify the feasibility and progressiveness of the scheme proposed in this paper by comparing the action behavior and external characteristics of the twin protection and the actual protection device. The presented research can provide a reference for further in-depth research and application of relay protection using digital means.

Abstract:Owing to their fexibility and rapid response, grid-connected distributed energy resources (DERs) are wielding growing infuence in frequency regulation markets (FRMs). Nevertheless, compared with conventional large-scale generators, small-scale DERs are usually weakly shielded by cyber security measures. This ofers attackers the opportunity of disrupting the clearing and settlement of FRMs by manipulating the bid information of DERs. In this paper, the frequency regulation market equilibrium is studied considering the dynamic gaming between attackers and defenders, both of which need the knowledge of FRMs for their interventions. Specifcally, a tri-level programming model characterizing the attacker–defender–operator (ADO) interdiction problem in FRMs is developed and then analyzed using a column and constraint generation algorithm, thereby achieving market equilibrium representing the defender’s best response to the attacker. The defense strategy in the market equilibrium can attenuate the negative infuence of cyber attacks upon the FRMs to the maximum extent. Finally, based on the operating rules of the California Independent System Operator, the FRM process considering the ADO interdiction is simulated and the numerical equilibrium results are presented.

Abstract:Accurate evaluation of power losses in a modular multilevel converter (MMC) is very important for circuit component selection, cooling system design, and reliability analysis of power transmission systems. However, the existing converter valve loss calculation methods using the nearest level modulation (NLM) method and the traditional sortingbased capacitor voltage balancing strategy are inaccurate since the submodule (SM) switching logics in the MMC arms are uncertain. To solve this problem, the switching principle of the SMs in the sorting-based voltage balancing strategy is analyzed. An accurate MMC power loss calculation method based on the analysis of loss distribution of various SM topologies, including half-bridge submodule (HBSM), full-bridge submodule (FBSM) and clamp double submodule (CDSM), is proposed in this paper. The method can accurately calculate the losses caused by the extra switching actions during the capacitor voltage balancing process, thus greatly increasing the calculation accuracy of switching losses compared with existing methods. Simulation results based on a practical±350 kV/1000 MW MMC-HVDC system with variety of MMC topologies with diferent voltage balancing strategies demonstrate the efectiveness of the proposed method.

Abstract:In this paper, a virtual synchronous generator (VSG) controller is applied to a hybrid energy storage system (HESS) containing a battery energy storage system and supercapacitor storage system for maintaining the frequency stability of an isolated microgrid. The microgrid contains a photovoltaic generation system and a diesel generator in addition to the HESS and two constant impedance loads that are fed through a medium voltage radial feeding system. The adaptive virtual inertia constant (H) with constant virtual damping coefcient (D) based on‘ bang-bang’ control for the microgrid’s frequency stability enhancement is investigated and compared with the constant parameter VSG. In addition, the bang-bang control is modifed to adapt the D beside the adaptive H, and the system response is investigated and compared with the conventional adaptive H technique. The VSG parameters are evaluated based on two diferent methods. The frst is a computational method based on the simplifed small signal stability analysis, while the other is based on an optimization method using two diferent objective functions and the particle swarm optimization technique. This paper also investigates the superiority of the proposed technique compared to other techniques in enhancing frequency stability, accelerating steady-state frequency restoration, and reducing the energy requirement of the HESS. The required power from the HESS is shared between the two energy storages using the low pass flter technique so as to reduce battery peak current

Abstract:To maximize improving the tracking wind power output plan and the service life of energy storage systems (ESS), a control strategy is proposed for ESS to track wind power planning output based on model prediction and two-layer fuzzy control. First, based on model predictive control, a model with deviations of grid-connected power from the planned output and the minimum deviation of the remaining capacity of the ESS from the ideal value is established as the target. Then, when the grid-connected power exceeds the allowable deviation band of tracking, the weight coefcients in the objective function are adjusted by introducing the frst layer of fuzzy control rules, combining the state of charge (SOC) of the ESS with the dynamic tracking demand of the planned value of wind power. When the grid-connected power is within the tracking allowable deviation band, the second layer of fuzzy control rules is used to correct the charging and discharging power of the ESS to improve its ability to track the future planned deviation while not crossing the limit. By repeatedly correcting the charging and discharging power of the ESS, its safe operation and the multitasking execution of the wind power plan output tracking target are ensured. Finally, taking actual data from a wind farm as an example, tests on a simulation platform of a combined wind-storage power generation system verify the feasibility and superiority of the proposed control strategy

Abstract:Transient stability is the key aspect of power system dynamic security assessment, and data-driven methods are becoming alternative measures of assessment. The current data-driven methods only construct correlations between variables while neglecting causal relationships. Therefore, they face problems such as poor robustness, which restrict their practical application. This paper introduces an improved constraint-inference approach for causality exploration of power system transient stability. Firstly, a causal structure discovery method of power system transient stability is proposed based on a PC-IGCI algorithm, which addresses the shortage caused by Markov equivalence and massive variables. Then, a relative average causal efect index is proposed to reveal the relationship between relative intervention strength and causal efects. The results of a case study verify that the proposed method can identify the causal structure between the transient stability variables entirely based on data. In addition, the causal efect sorting between“cause” and“outcome” of transient stability variables is revealed. This paper provides a new approach for data mining to uncover the causal mechanisms between variables in power systems and expand the capabilities of data-driven methods in power system application.

Abstract:To facilitate wind energy use and avoid low returns, or even losses in extreme cases, this paper proposes an integrated risk measurement and control approach to jointly manage multiple statistical properties of the expected proft distribution for a wind storage system. First, a risk-averse stochastic decision-making framework and multi-type risk measurements, including the conditional value at Risk (CVaR), value at risk (VaR) and shortfall probability (SP), are described in detail. To satisfy the various needs of multi-type risk-averse decision makers, integrated risk measurement and control approaches are then proposed by jointly considering the expected, boundary and probability values of the extreme results. These are managed using CVaR, VaR and SP, respectively. Finally, the efectiveness of the proposed risk control strategy is verifed by conducting case studies with realistic market data, and the results of diferent risk control strategies are analyzed in depth. The impacts of the risk parameters of the decision maker, the energy capacity of the battery storage and the price diference between the day-ahead and real-time markets on the expected profts and risks are investigated in detail

Abstract:Natural gas is the main energy source and carbon emission source of integrated energy systems (IES). In existing studies, the price of natural gas is generally fxed, and the impact of price fuctuation which may be brought by future liberalization of the terminal side of the natural gas market on the IES is rarely considered. This paper constructs a natural gas price fuctuation model based on particle swarm optimization (PSO) and Dynamic Bayesian networks (DBN) algorithms. It uses the improved epsilon constraint method and fuzzy multi-weight technology to solve the Pareto frontier set considering the system operation cost and carbon emission. The system operation cost is described using Latin Hypercube Sampling (LHS) to predict the stochastic output of the renewable energy source, and a penalty function based on the Predicted Mean Vote (PMV) model to describe the thermal comfort of the user. This is analyzed using the Grey Wolf Optimization (GWO) algorithm. Carbon emissions are calculated using the carbon accounting method, and a ladder penalty mechanism is introduced to defne the carbon trading price. Results of the comparison illustrate that the Pareto optimal solution tends to choose less carbon emission, electricity is more economical, and gas is less carbon-intensive in a small IES for end-users when the price of natural gas fuctuates. The impacts of various extents of natural gas price fuctuation for the same load are also discussed.

Abstract:With the deregulation of electricity market in distribution systems, renewable distributed generations (RDG) are being invested in by third-party social capital, such as distributed generations operators (DGOs) and load aggregators (LAs). However, their arbitrary RDG investment and electricity trading behavior can bring great challenges to distribution system planning. In this paper, to reduce distribution system investment, a distribution system expansion planning model based on a bi-level Stackelberg game is proposed for the distribution system operator (DSO) to guide this social capital to make suitable RDG investment. In the proposed model, DSO is the leader, while DGOs and LAs are the followers. In the upper level, the DSO determines the expansion planning scheme including investments in substations and lines, and optimizes the variables provided for followers, such as RDG locations and contract prices. In the lower level, DGOs determine the RDG capacity and electricity trading strategy based on the RDG locations and contract prices, while LAs determine the RDG capacity, demand response and electricity trading strategy based on contract prices. The capacity information of the DRG is sent to the DSO for decision-making on expansion planning. To reduce the cost and risk of multiple agents, two long-term renewable energy contracts are introduced for the electricity trading. Conditional value-at-risk method is used to quantify the RDG investment risk of DGOs and LAs with diferent risk preferences. The efectiveness of the proposed model and method is verifed by studies using the Portugal 54-bus system.

Abstract:The operational performance of conventional overcurrent protection relay coordination connected to a distribution network is adversely afected by the penetration of distributed generators (DG) at diferent buses in the network. To address this problem, this paper proposes a novel adaptive protection coordination scheme using a radial basis function neural network (RBFNN), which automatically adjusts the overcurrent relay settings, i.e., time setting multiplier (TSM) and plug setting multiplier (PSM) based on the penetration of DGs. Short circuit currents and voltages measured at diferent buses are acquired using the remote terminal units (RTU) connected to diferent buses within the terminal network. Communication between the various remotes and local end station RTUs is through hybrid communication systems of fber optic and power line communication system modules. The new adaptive overcurrent protection scheme is applied to the IEEE 33-bus distribution network with and without DGs, for single and multi-DG penetration using both the ETAP and MATLAB software. The simulation results show the proposed scheme signifcantly improves the protection coordination.

Abstract:This paper proposes a discrete space vector modulation and optimized switching sequence model predictive controller for three-level neutral-point-clamped inverters in grid-connected applications. The proposed strategy is based on cascaded model predictive control (MPC) for controlling the grid current while maintaining the capacitor voltage balanced without weighting factor. To enhance the closed-loop performance, the external MPC evaluates 19 basic and 138 virtual vectors (VV) of the proposed space vector method. The optimal control voltage is then selected using an extended deadbeat method to reduce the execution time of the proposed control algorithm. By using the discrete space vector modulation principle, the VV are synthesized based on switching sequence (SS) and are divided into negative and positive SSs considering their impact on the neutral point (NP) potential. The inner MPC evaluates both types of SSs and selects the one that keeps the capacitor voltage balanced. Various controllers are evaluated and compared against the proposed control strategy. The results show that the proposed strategy improves performance without weighting factor, while maintaining a total harmonic distortion of current to be less than 2%. Compared to the modulated MPC which provides the same fxed switching frequency, the proposed controller reduces the computational burden by over 50% while also providing better NP voltage balance accuracy