Abstract:Under perfect competition, marginal pricing results in short-term efficiency and the subsequent right short-term price signals. However, the main reason for the adoption of marginal pricing is not the above, but investment cost recovery, that is the fact that the profits obtained by infra-marginal technologies (technologies whose production cost is below the marginal price) allow them just to recover their investment costs. In addition, if the perfect competition assumption is removed, investment over-recovery or under-recovery generally occurs for infra-marginal technologies.

Abstract:The European electricity and gas markets have been deregulated more than two decades before. From rather diverse starting points, they have continuously evolved over the years to accommodate with new challenges and to improve integration. Since 2005, these markets have been complemented by the market for emission certificates established by the European Union (EU) emission trading system. Three partly competing paradigms have thereby shaped the markets and continue to drive their on-going transformation: effective competition, subsidiarity and sustainability.

Abstract:Should the organization, design and functioning of electricity markets be taken for granted? Definitely not. While decades of evolution of electricity markets in countries that committed early to restructure their electric power sector made us believe that we may have found the right and future-proof model, the substantially and rapidly evolving context of our power and energy systems is challenging this idea in many ways. Actually, that situation brings both challenges and opportunities. Challenges include accommodation of renewable energy generation, decentralization and support to investment, while opportunities are mainly that advances in technical and social sciences provide us with many more options in terms of future market design. We here take a holistic point of view, by trying to understand where we are coming from with electricity markets and where we may be going. Future electricity markets should be made fit for purpose by considering them as a way to organize and operate a socio-techno-economic system.

Abstract:With an increase in the electrification of end-use sectors, various resources on the demand side provide great flexibility potential for system operation, which also leads to problems such as the strong randomness of power consumption behavior, the low utilization rate of flexible resources, and difficulties in cost recovery. With the core idea of “access over ownership”, the concept of the sharing economy has gained substantial popularity in the local energy market in recent years. Thus, we provide an overview of the potential market design for the sharing economy in local energy markets (LEMs) and conduct a detailed review of research related to local energy sharing, enabling technologies, and potential practices. This paper can provide a useful reference and insights for the activation of demand-side flexibility potential. Hopefully, this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.

Abstract:Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges. The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems (CPPSs). This paper presents a comprehensive review of some of the latest attack detection and defense strategies. Firstly, the vulnerabilities brought by some new information and communication technologies (ICTs) are analyzed, and their impacts on the security of CPPSs are discussed. Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework, and their features and negative impacts are discussed. Secondly, two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed, and their benefits and drawbacks are discussed. Moreover, two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed. Finally, the trends and challenges in attack detection and defense strategies in CPPSs are provided.

Abstract:Increasing penetration of renewable energy generation poses a challenge to power system inertia adequacy. It is vital to provide long-term incentive signals to induce a generation mix with adequate inertia supply. However, existing literature rarely studies inertia incentive mechanisms or considers inertia constraints when making generation investment decisions. Thus, we propose an inertia market to quantify the value of inertia and to remunerate inertia provision. To examine the impacts of the inertia market on generation mix, we then propose a stochastic bilevel generation investment equilibrium model that depicts a multi-leader and multi-follower Stackelberg game. The lower level of the model considers the proposed inertia market, along with the energy, reserve, and capacity markets. The upper level considers multiple profit-maximizing strategic producers, and each producer is able to build gas-fired generators, wind generators, and energy storages. Numerical experiments demonstrate that a generation mix with adequate inertia supply can be induced with the proposed inertia market whereas there can be inertia shortage without the inertia market. Interestingly, considering carbon taxes, it is more cost-competitive to invest in wind resources with virtual inertia facilities than to substitute wind resources by thermal generators. Correspondingly, the introduction of an inertia market does not significantly reduce wind generation shares but boosts virtual inertia facility penetration. Our findings imply a future power system powered by fully decarbonized power resources with adequate inertia.

Abstract:This paper addresses two issues that concern the electricity market participants under the European day-ahead market (DAM) framework, namely the feasibility of the attained schedules and the non-confiscation of cleared volumes. To address the first issue, new resource-specific orders, i.e., thermal orders for thermal generating units, demand response orders for load responsive resources, and energy limited orders for storage resources, are proposed and incorporated in the existing European DAM clearing problem. To address the second issue, two approaches which lead to a non-confiscatory market are analyzed① discriminatory pricing with side-payments (U.S. paradigm); and ② non-discriminatory pricing excluding out-of-money orders (European paradigm). A comparison is performed between the two approaches to investigate the most appropriate pricing rule in terms of social welfare, derived revenues for the sellers, and efficiency of the attained results. The proposed model with new resource-specific products is evaluated in a European test system, achieving robust solutions. The feasibility of the attained schedules is demonstrated when using resource-specific orders compared with block orders. Finally, the results indicate the supremacy of discriminatory pricing with side-payments compared with the current European pricing rule.

Abstract:With the development of smart home energy management technology, prosumers are endowed with increased initiative in peer-to-peer (P2P) transactions, bringing new potential for cost savings. In this study, a novel strategic P2P energy trading framework is proposed considering the impact of network constraints on personal transaction strategies. Prosumers can estimate the allowed power injection before engaging in the P2P energy trading, which is solved in a distributed manner based on the sharing form alternating direction method of multipliers (ADMM) algorithm. To quantify the network usage cost for each prosumer and promote local transactions among prosumers at the same bus, a modified continuous double auction (CDA) matching algorithm is proposed including a transaction fee. An adaptive aggressiveness-based bidding strategy is generated considering the risk of uncertainty in real-time energy delivery amount under the limitations of the distribution network. The proposed strategic P2P energy trading framework is tested with the IEEE 37-bus distribution network and it is effective in creating profits for prosumers and supporting distribution network operations.

Abstract:This paper proposes a novel approach for the provision of non-frequency ancillary service (AS) by consumers connected to low-voltage distribution networks. The proposed approach considers an asymmetric pool-based local market for AS negotiation, allowing consumers to set a flexibility quantity and desired price to trade. A case study with 98 consumers illustrates the proposed market-based non-frequency AS provision approach. Also, three different strategies of consumers’ participation are implemented and tested in a real low-voltage distribution network with radial topology. It is shown that consumers can make a profit from the sale of their flexibility while contributing to keeping the network power losses, voltage, and current within pre-defined limits. Ultimately, the results demonstrate the value of AS coming directly from end-users.

Abstract:This study presents the assumptions and strategies for the practical implementation of the dynamic mode decomposition approach in the wide-area monitoring system of the Italian transmission system operator, Terna. The procedure setup aims to detect poorly damped interarea oscillations of power systems. Dynamic mode decomposition is a data-driven technique that has gained increasing attention in different fields; the proposed implementation can both characterize the oscillatory modes and identify the most influenced areas. This study presents the results of its practical implementation and operational experience in power system monitoring. It focuses on the main characteristics and solutions identified to reliably monitor the interarea electromechanical modes of the interconnected European power system. Moreover, conditions to issue an appropriate alarm in case of critical operating conditions are described. The effectiveness of the proposed approach is validated by its application in three case studies: a critical oscillatory event and a short-circuit event that occurred in the Italian power system in the previous years, and a 15-min time interval of normal grid operation recorded in March 2021.

Abstract:To completely eliminate the time delays caused by phasor data compressions for real-time synchrophasor applications, a real-time synchrophasor data compression (RSDC) is proposed in this paper. The two-way rotation characteristic and elliptical trajectory of dynamic synchrophasors are introduced first to enhance the compressions along with a fast solving method for elliptical trajectory fitting equations. The RSDC for phasor data compression and reconstruction is then proposed by combining the interpolation and extrapolation compressions. The proposed RSDC is verified by both the actual phasor measurement data recorded in a two-phase short-circuit incident and a subsynchronous oscillation incident, and the synthetic dynamic synchrophasors. It is also compared with two previous real-time phasor data compression techniques, i.e., phasor swing door trending (PSDT) and exception and swing door trending (SDT) data compression (ESDC). The verification results demonstrate that RSDC can achieve significantly higher compression ratios for offline applications with the interpolation and the zero-delay phasor data compression with the extrapolation for real-time applications simultaneously.

Abstract:In recent years, subsynchronous control interaction (SSCI) has frequently taken place in renewable-connected power systems. To counter this issue, utilities have been seeking tools for fast and accurate identification of SSCI events. The main challenges of SSCI monitoring are the time-varying nature and uncertain modes of SSCI events. Accordingly, this paper presents a simple but effective method that takes advantage of intrinsic time-scale decomposition (ITD). The main purpose is to improve the accuracy and robustness of ITD by incorporating the least-squares method. Results show that the proposed method strikes a good balance between dynamic performance and estimation accuracy. More importantly, the method does not require any prior information, and its performance is therefore not affected by the frequency constitution of the SSCI. Comprehensive comparative studies are conducted to demonstrate the usefulness of the method through synthetic signals, electromagnetic temporary program (EMTP) simulations, and field-recorded SSCI data. Finally, real-time simulation tests are conducted to show the feasibility of the method for real-time monitoring.

Abstract:The grid-connection of large-scale and high-penetration wind power poses challenges to the friendly dispatching control of the power system. To coordinate the complicated optimal dispatching and rapid real-time control, this paper proposes a hierarchical cluster coordination control (HCCC) strategy based on model predictive control (MPC) technique. Considering the time-varying characteristics of wind power generation, the proposed HCCC strategy constructs an improved multi-time-scale active power dispatching model, which consists of five parts: formulation of cluster dispatching plan, rolling modification of intra-cluster plan, optimization allocation of wind farm (WF), grouping coordinated control of wind turbine group (WTG), and real-time adjustment of single-machine power. The time resolutions are sequentially given as 1 hour, 30 min, 15 min, 5 min, and 1 min. In addition, a combined predictive model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), wavelet thresholding (WT), and least squares support vector machine (LSSVM) is established. The fast predictive feature of this model cooperates with the HCCC strategy that effectively improves the predictive control precision. Simulation results show that the proposed HCCC strategy enables rapid response to active power control (APC), and significantly improves dispatching control accuracy and wind power accommodation capabilities.

Abstract:The distributed capacitance of the line becomes larger as the scale of wind farms, the transmission voltage level, and the transmission distance increase. Hence, the error of the traditional time-domain distance protection scheme based on the R-L model, which ignores the distributed capacitance of the line, becomes unacceptable. Therefore, the error of the time-domain fault location method based on the R-L model, especially the maximum error range, is theoretically analyzed in this paper. On this basis, a novel fault location method based on the R-L and Bergeron models is proposed. Then, a fast time-domain distance protection scheme is designed. In the proposed scheme, the error in the fitting calculation is used to construct a weight matrix, and an algorithm for solving the time-domain differential equations is designed to improve the calculation speed and stability. Compared with the traditional frequency-domain distance protection scheme, the proposed scheme is independent of the power supply characteristics; thus, it is suitable for wind farm transmission lines. In addition, compared with the traditional method based on the R-L model, the proposed scheme effectively avoids the negative influence of the distributed capacitance of the line, which significantly improves the operating speed. Different types of faults are simulated by PSCAD/EMTDC to verify the effectiveness and superiority of the proposed scheme.

Abstract:Optimal torque (OT) control is a widely used method for maximum power point tracking (MPPT) due to its simplicity. In order to overcome the adverse impacts of turbulent wind speed variations on MPPT, in several methods, modification factors have been proposed to dynamically modify the ideal power curve for OT control. However, this paper finds that the update cycles used in existing methods to adjust power curve modification factors are very long and hence these factors are difficult to be updated in a timely manner along with the wind speed variations. This thereby may deteriorate the effectiveness of wind energy extraction. Therefore, an optimal decreased torque gain (DTG) control method is proposed in this paper. Based on the persistence method, an offline mapping from the wind speed and rotor speed to optimal modification factors is established via optimal control theory. The power curve can be periodically modified online through the mapping relationship. In this method, the update cycles for these power curve modification factors are shortened from tens of minutes to seconds. The simulations and experiments show that the proposed method is more efficient than others in terms of energy extraction under varying wind speeds, especially for turbulent wind cases.

Abstract:In this paper, a new proposal for the implementation of the well-known direct power control (DPC) technique in grid-connected photovoltaic (PV) systems is suggested. Normally, the DPC is executed using a look-up table procedure based on the error between the actual and reference values of the active and reactive power. Thus, the structure of the DPC is simple and results in a fast transient behavior of the inner current loop (injected currents). Therefore, in the current study, the DPC is reformulated using a dead-beat function. In this formulation, the reference voltage vector (RVV) is obtained in the α-β reference frame. Consequently, the switching states for the inverter can be obtained based on the sign of the components of the RVV. The suggested DPC is compared with the conventional one and other switching tables, which are intended for performance enhancement. Furthermore, an extended Kalman filter (EKF) is utilized to eliminate all grid-voltage sensors. Moreover, the switching frequency of the proposed technique is minimized without any need for weighting factors or cost function evaluation. The overall control technique is validated using a hardware-in-the-loop (HIL) experimental set-up and compared with other schemes under different operating conditions.

Abstract:Cooperation between electric power networks (EPNs) and district heating networks (DHNs) has been extensively studied under the assumption that all information exchanged is authentic. However, EPNs and DHNs belonging to different entities may result in marketing fraud. This paper proposes a cooperation mechanism for integrated electricity-heat systems (IEHSs) to overcome information asymmetry. First, a fraud detection method based on multiparametric programming with guaranteed feasibility reveals the authenticity of the information. Next, all honest entities are selected to form a coalition. Furthermore, to maintain operational independence and distribute benefits fairly, Benders decomposition is enhanced to calculate Shapley values in a distributed fashion. Finally, the cooperative surplus generated by the coalition is allocated according to the marginal contribution of each entity. Numerical results show that the proposed mechanism stimulates cooperation while achieving Pareto optimality under asymmetric information.

Abstract:By collecting and organizing historical data and typical model characteristics, hydrogen energy storage system (HESS)-based power-to-gas (P2G) and gas-to-power systems are developed using Simulink. The energy transfer mechanisms and numerical modeling methods of the proposed systems are studied in detail. The proposed integrated HESS model covers the following system components: alkaline electrolyzer (AE), high-pressure hydrogen storage tank with compressor (CM & H ₂ tank), and proton-exchange membrane fuel cell (PEMFC) stack. The unit models in the HESS are established based on typical U-I curves and equivalent circuit models, which are used to analyze the operating characteristics and charging/discharging behaviors of a typical AE, an ideal CM & H ₂ tank, and a PEMFC stack. The validities of these models are simulated and verified in the MicroGrid system, which is equipped with a wind power generation system, a photovoltaic power generation system, and an auxiliary battery energy storage system (BESS) unit. Simulation results in MATLAB/Simulink show that electrolyzer stack, fuel cell stack and system integration model can operate in different cases. By testing the simulation results of the HESS under different working conditions, the hydrogen production flow, stack voltage, state of charge (SOC) of the BESS, state of hydrogen pressure (SOHP) of the HESS, and HESS energy flow paths are analyzed. The simulation results are consistent with expectations, showing that the integrated HESS model can effectively absorb wind and photovoltaic power. As the wind and photovoltaic power generations increase, the HESS current increases, thereby increasing the amount of hydrogen production to absorb the surplus power. The results show that the HESS responds faster than the traditional BESS in the microgrid, providing a solid theoretical foundation for later wind-photovoltaic-HESS-BESS integration.

Abstract:This paper presents a controller for fast and ultra-fast electric vehicle (EV) charging stations. Without affecting the charging efficiency, the proposed controller enables the charger to provide support to the interconnection voltage to counter and damp its transients. Existing solutions are either hardware-based such as using supercapacitors and flywheels which increase the cost and bulkiness of the charging station, or software-based such as P/ V droop methods which are still unable to provide a robust and strong voltage support. This paper proposes an emulated supercapacitor concept in the control system of the ultra-fast EV charger in an islanded DC microgrid. Thus, it converts the EV from a static load to a bus voltage supportive load, leading to reduced bus voltage oscillations during single and multiple ultra-fast EV charging operations, and rides through and provides supports during extreme external disturbances. Detailed analysis and design guidelines of the proposed controller are presented, and its effectiveness and improved performance compared with conventional techniques are shown for different case studies.

Abstract:The single-line-to-ground faults with line breaks (SLGFs-LBs) occur more and more frequently in distribution networks and can cause major safety accidents. It is difficult to distinguish the single-line-to-ground faults (SLGFs) in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation conditions of distribution networks. This paper proposes a method for distinguishing SLGFs-LBs and SLGFs. First, the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed, and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion. Phasor measurement units (PMUs) are selected as measuring devices. Then, the effects of operation conditions and external devices in distribution networks on the proposed method are discussed, and the phase errors caused by them are calculated to correct the identification method. Finally, the field testing and simulation experiments are conducted to verify the effectiveness and robustness of the proposed method.

Abstract:This paper presents a novel fault detection and identification method for low-voltage direct current (DC) microgrid with meshed configuration. The proposed method is based on graph convolutional network (GCN), which utilizes the explicit spatial information and measurement data of the network topology to identify a fault. It has a more substantial feature extraction ability even in the presence of noise and bad data. The adjacency matrix for GCN is developed by considering the network topology as an inherent graph. The bus voltage and line current samples after faults are regarded as the node attributes. Moreover, the DC microgrid model is developed using PSCAD/EMTDC simulation, and fault simulation is carried out by considering different possible events that include environmental and physical conditions. The performance of the proposed method under different conditions is compared with those of different machine learning techniques such as convolutional neural network (CNN), support vector machine (SVM), and fully connected network (FCN). The results reveal that the proposed method is more effective than others at detecting and classifying faults. This method also possesses better robustness under the presence of noise and bad data.

Abstract:An advanced metering infrastructure (AMI) system plays a key role in the smart grid (SG), but it is vulnerable to cyberattacks. Current detection methods for AMI cyberattacks mainly focus on the data center or a distributed independent node. On one hand, it is difficult to train an excellent detection intrusion model on a self-learning independent node. On the other hand, large amounts of data are shared over the network and uploaded to a central node for training. These processes may compromise data privacy, cause communication delay, and incur high communication costs. With these limitations, we propose an intrusion detection method for AMI system based on federated learning (FL). The intrusion detection system is deployed in the data concentrators for training, and only its model parameters are communicated to the data center. Furthermore, the data center distributes the learning to each data concentrator through aggregation and weight assignments for collaborative learning. An optimized deep neural network (DNN) is exploited for this proposed method, and extensive experiments based on the NSL-KDD dataset are carried out. From the results, this proposed method improves detection performance and reduces computation costs, communication delays, and communication overheads while guaranteeing data privacy.

Abstract:To improve the equivalent inertia of DC microgrids (DCMGs), a unified control is proposed for the first time for a bi-directional DC-DC converter based super-capacitor (SC) system, whereby power smoothing and SC terminal voltage regulation can be achieved in a DCMG simultaneously. The proposed control displays good plug-and-play features using only local measurements. For quantitative analysis and effective design of the critical parameter of unified control, two indices, equivalent power supporting time and inertia contributed by the unified controlled SC system, are introduced firstly. Then, with a simple but effective reduced-order model of a DCMG, analytical solutions are obtained for the two indices. In addition, a systematic design method is presented for the proposed unified control. Finally, to verify the proposed unified control, a switching model is developed for a typical DCMG in PSCAD/EMTDC, and theoretical analyses are conducted for different operating conditions.

Abstract:The over-current capacity of half-bridge modular multi-level converter (MMC) is quite weak, which requests protections to detect faults accurately and reliably in several milliseconds after DC faults. The sensitivity and reliability of the existing schemes are vulnerable to high resistance and data errors. To improve the insufficiencies, this paper proposes a pilot protection scheme by using the random matrix for DC lines in the symmetrical bipolar MMC high-voltage direct current (HVDC) grid. Firstly, the 1-mode voltage time-domain characteristics of the line end, DC bus, and adjacent line end are analyzed by the inverse Laplace transform to find indicators of fault direction. To combine the actual model with the data-driven method, the methods to construct the data expansion matrix and to calculate additional noise are proposed. Then, the mean spectral radiuses of two random matrices are used to detect fault directions, and a novel pilot protection criterion is proposed. The protection scheme only needs to transmit logic signals, decreasing the communication burden. It performs well in high-resistance faults, abnormal data errors, measurement errors, parameters errors, and different topology conditions. Numerous simulations in PSCAD/EMTDC confirm the effectiveness and reliability of the proposed protection scheme.

Abstract:Grid-forming control (GFC) is promising for power electronics based power systems with high renewable energy penetration. Naturally, the impedance modeling for GFC is necessary and has gained significant attention recently. However, most of the impedance analyses for GFC are based on a two-level converter (TLC) rather than a modular multilevel converter (MMC). MMC differs from TLC with respect to its dominant multi-frequency response. It is necessary to analyze the impedance of GFC-based MMC owing to its superiority in high-voltage direct current (HVDC) transmission to interlink two weak AC systems with high renewable energy penetration. As the main contribution, this paper presents the AC- and DC-side impedance analyses for the GFC-based MMC with both power and DC voltage control using the harmonic transfer function (HTF), and compares the impedances of GFC-based MMC and TLC. It is inferred that although the impedance is mainly influenced within 200 Hz, the instability still could occur owing to negative resistance triggered by relatively larger parameters. The difference in AC-side impedance with power and DC voltage control is not apparent with proper parameters, while the DC-side impedance differs significantly. The generalized Nyquist criterion is necessary for AC-side stability owing to the relatively large coupling terms under GFC. Moreover, the coupling between AC- and DC-side impedances is noneligible, especially considering the DC-side resonance around the system resonant peak. The effects of parameters, system strength, and virtual impedance on the impedance shaping are analyzed and verified through simulations.

Abstract:Voltage source converter based high-voltage direct current (VSC-HVDC) transmission technology has been extensively employed in power systems with a high penetration of renewable energy resources. However, connecting a voltage source converter (VSC) to an AC weak grid may cause the converter system to become unstable. In this paper, a phase-shift phase-locked loop (PS-PLL) is proposed wherein a back electromotive force (BEMF) observer is added to the conventional phase-locked loop (PLL). The BEMF observer is used to observe the voltage of the infinite grid in the stationary αβ frame, which avoids the problem of inaccurate observations of the grid voltage in the dq frame that are caused by the output phase angle errors of the PLL. The VSC using the PS-PLL can operate as if it is facing a strong grid, thus enhancing the stability of the VSC-HVDC system. The proposed PS-PLL only needs to be properly modified on the basis of a traditional PLL, which makes it easy to implement. In addition, because it is difficult to obtain the exact impedance of the grid, the influence of short-circuit ratio (SCR) estimation errors on the performance of the PS-PLL is also studied. The effectiveness of the proposed PS-PLL is verified by the small-signal stability analysis and time-domain simulation.

Abstract:This paper proposes a single-ended fault detection scheme for long transmission lines using support vector machine (SVM) for multi-terminal direct current systems based on modular multilevel converter (MMC-MTDC). The scheme overcomes existing detection difficulties in the protection of long transmission lines resulting from high grounding resistance and attenuation, and also avoids the sophisticated process of threshold value selection. The high-frequency components in the measured voltage extracted by a wavelet transform and the amplitude of the zero-mode set of the positive-sequence voltage are the inputs to a trained SVM. The output of the SVM determines the fault type. A model of a four-terminal DC power grid with overhead transmission lines is built in PSCAD/EMTDC. Simulation results of EMTDC confirm that the proposed scheme achieves 100% accuracy in detecting short-circuit faults with high resistance on long transmission lines. The proposed scheme eliminates mal-operation of DC circuit breakers when faced with power order changes or AC-side faults. Its robustness and time delay are also assessed and shown to have no perceptible effect on the speed and accuracy of the detection scheme, thus ensuring its reliability and stability.

Abstract:The series line-commutated converter (LCC) and modular multilevel converter (MMC) hybrid high-voltage direct current (HVDC) system provides a more economical and flexible alternative for ultra-HVDC (UHVDC) transmission, which is the so-called Baihetan-Jiangsu HVDC (BJ-HVDC) project of China. In one LCC and two MMCs (1+2) operation mode, the sub-module (SM) capacitors suffer the most rigorous overvoltage induced by three-phase-to-ground fault at grid-side MMC and valve-side single-phase-to-ground fault in internal MMC. In order to suppress such huge overvoltage, this paper demonstrates a novel alternative by employing the MMC-based embedded battery energy storage system (MMC-BESS). Firstly, the inducements of SM overvoltage are analyzed. Then, coordinated with MMC-BESS, new fault ride-through (FRT) strategies are proposed to suppress the overvoltage and improve the FRT capability. Finally, several simulation scenarios are carried out on PSCAD/EMTDC. The overvoltage suppression is verified against auxiliary device used in the BJ-HVDC project in a monopolar BJ-HVDC system. Further, the proposed FRT strategies are validated in the southern Jiangsu power grid of China based on the planning data in the summer of 2025. Simulation results show that the MMC-BESS and proposed FRT strategies could effectively suppress the overvoltage and improve the FRT capability.

Abstract:Virtual power plants (VPPs) including distributed generation, energy storage, and elastic load are emerging in distribution networks. Multiple VPPs can participate in electricity market as an aggregated entity and effective cost allocation mechanism among VPPs is a crucial issue. This paper focuses on allocating ex-post cost of VPPs incurred by deviation between actual power and ex-ante schedule in a two-settlement electricity market. We obtain approximate quadratic formulation of ex-post deviation cost considering network loss and develop an analytical cost allocation algorithm based on cooperative game theory. The allocated cost is consistent with cost causation principle and provides VPPs with incentive for aggregation. The proposed allocation method and relevant theoretical result are evaluated and verified by numerical tests.

Abstract:For the safe and fast recovery of line commutated converter based high-voltage direct current (LCC-HVDC) transmission systems after faults, a DC current order optimization based strategy is proposed. Considering the constraint of electric and control quantities, the DC current order with the maximum active power transfer is calculated by Thevenin equivalent parameters (TEPs) and quasi-state equations of LCC-HVDC transmission systems. Meanwhile, to mitigate the subsequent commutation failures (SCFs) that may come with the fault recovery process, the maximum DC current order that avoids SCFs is calculated through imaginary commutation process. Finally, the minimum value of the two DC current orders is sent to the control system. Simulation results based on PSCAD/EMTDC show that the proposed strategy mitigates SCFs effectively and exhibits good performance in recovery.