Abstract:The increasing trend for integrating renewable energy sources into the grid to achieve a cleaner energy system is one of the main reasons for the development of sustainable microgrid (MG) technologies. As typical power-electronized power systems, MGs make extensive use of power electronics converters, which are highly controllable and flexible but lead to a profound impact on the dynamic performance of the whole system. Compared with traditional large-capacity power systems, MGs are less resistant to perturbations, and various dynamic variables are coupled with each other on multiple timescales, resulting in a more complex system in-stability mechanism. To meet the technical and economic challenges, such as active and reactive power-sharing, volt-age, and frequency deviations, and imbalances between power supply and demand, the concept of hierarchical control has been introduced into MGs, allowing systems to control and manage the high capacity of renewable energy sources and loads. However, as the capacity and scale of the MG system increase, along with a multi-timescale control loop design, the multi-timescale interactions in the system may become more significant, posing a serious threat to its safe and stable operation. To investigate the multi-timescale behaviors and instability mechanisms under dynamic inter-actions for AC MGs, existing coordinated control strategies are discussed, and the dynamic stability of the system is defined and classified in this paper. Then, the modeling and assessment methods for the stability analysis of multi-timescale systems are also summarized. Finally, an outlook and discussion of future research directions for AC MGs are also presented.

Abstract:If a failure in the components of a photovoltaic (PV) system, such as PV module, controller, inverter, load, cable, etc. goes undetected and uncorrected, it can seriously affect the efficiency, safety, and reliability of the entire PV power plant. In addition, fires can occur if specific faults, such as arc, ground, and line-to-line faults remain unresolved. Therefore, PV system (PVS) fault diagnoses are crucial for PV power plant reliability, efficiency, and safety. Many fault diagnosis methods and techniques for PVS components have been developed. In addition, with the development of PV devices, more advanced and intelligent diagnostic technologies are continuously being researched and developed. However, a systematic and thorough analysis, summary, and conclusion are still urgently required. Thus, this paper introduces the types, causes, and impacts of PVS faults, and reviews and discusses the methods proposed in the literature for PVS fault diagnosis, and in particular, failures in PV arrays. Special attention is paid to the optimization direction of various fault diagnosis methods under different priorities, and their limitations, feasibility, complexity, and cost-effectiveness. Finally, challenges and suggestions are put forward for future research.

Abstract:The occurrence of power flow reversal and off-limit of the voltage on common bus becomes more frequent because of the increasing penetration of renewable energy sources (RES) in microgrids. To guarantee the safe and stable operation, adjusting the power output of RES-based inverters to avoid the off-limit voltage is necessary. Considering the apparent power characteristics of inverters, as well as the minimum participation of active power, a voltage control strategy based on stage division to be within the voltage limit is investigated in this paper. In the case of unknown demand and distribution of loads, the proposed control strategy is able to make full use of the apparent power to regulate voltage using simple calculations, while the performance in economical operation is satisfactory. Simulation results prove the effectiveness of the proposed method on the common bus off-limit voltage adjustment.

Abstract:As one of the new generation flexible AC transmission systems (FACTS) devices, the interline power flow controller (IPFC) has the significant advantage of simultaneously regulating the power flow of multiple lines. Nevertheless, how to choose the appropriate location for the IPFC converters has not been discussed thoroughly. To solve this problem, this paper proposes a novel location method for IPFC using entropy theory. To clarify IPFC's impact on system power flow, its operation mechanism and control strategies of different types of serial converters are discussed. Subsequently, to clarify the system power flow characteristic suitable for device location analysis, the entropy concept is introduced. In this process, the power flow distribution entropy index is used as an optimization index. Using this index as a foundation, the power flow transfer entropy index is also generated and proposed for the IPFC location determination study. Finally, electromechanical electromagnetic hybrid simulations based on ADPSS are implemented for validation. These are tested in a practical power grid with over 800 nodes. A modular multilevel converter (MMC)-based IPFC electromagnetic model is also established for precise verification. The results show that the proposed method can quickly and efficiently complete optimized IPFC location and support IPFC to determine an optimal adjustment in the N-1 fault cases.

Abstract:This paper investigates a double auction-based peer-to-peer (P2P) energy trading market for a community of renewable prosumers with private information on reservation price and quantity of energy to be traded. A novel competition padding auction (CPA) mechanism for P2P energy trading is proposed to address the budget deficit problem while holding the advantages of the widely-used Vickrey-Clarke-Groves mechanism. To illustrate the theoretical properties of the CPA mechanism, the sufficient conditions are identified for a truth-telling equilibrium with a budget surplus to exist, while further proving its asymptotical economic efficiency. In addition, the CPA mechanism is implemented through consortium blockchain smart contracts to create safer, faster, and larger P2P energy trading markets. The proposed mechanism is embedded into blockchain consensus protocols for high consensus efficiency, and the budget surplus of the CPA mechanism motivates the prosumers to manage the blockchain. Case studies are carried out to show the effectiveness of the proposed method.

Abstract:With advances in modern agricultural parks, the rural energy structure has undergone profound change, leading to the emergence of an agricultural energy internet. This integrated system combines agricultural energy utilization, the information internet, and agricultural production. Accordingly, this study proposes a regulation flexibility assessment approach and optimal aggregation strategy of greenhouse loads (GHLs) for modern agricultural parks. First, taking into account the operational characteristics of typical GHLs, refined load demand models for lighting, humidification, and temperature-controlled loads are established. Secondly, the recursive least squares method-based parameter identification method is designed to accurately determine key GHL model parameters. Finally, based on the regulation flexibility of quantitatively evaluated GHLs, GHLs are optimally aggregated into multiple flexible aggregators considering minimal operational cost and greenhouse environmental constraints. The results indicate that the proposed regulation flexibility assessment approach and optimal aggregation strategy of GHLs can alleviate the peak regulation pressure on power grids by flexibly shifting the load demands of GHLs.

Abstract:In multi-fed grid-connected systems, there are complex dynamic interactions between different pieces of equipment. Particularly in situations of weak-grid faults, the dynamic coupling between equipment becomes more pronounced. This may cause the system to experience small-signal instability during the fault steady-state. In this paper, multi-paralleled doubly fed induction generator (DFIG)-based wind farms (WFs) are taken as an example to study the dynamic coupling within a multi-fed system during fault steady-state of symmetrical low voltage ride-through (LVRT) in a weak grid. The analysis reveals that the dynamic coupling between WFs will introduce a damping shift to each WF. This inevitably affects the system's dynamic stability and brings the risk of small-signal instability during fault steady-state in LVRT scenarios. Increasing the distance to fault location and fault severity will exacerbate the dynamic coupling between WFs. Because of the dynamic coupling, adjusting the control state of one WF will affect the stability of the remaining WFs in the system. Hence, a cooperative control strategy for multi-paralleled DFIG WFs is proposed to improve dynamic stability during LVRT. The analysis and the effectiveness of the proposed control strategy are verified by modal analysis and simulation.

Abstract:The rapid development of communication services in the power distribution network poses challenges for existing wireless communications, and the deployment of a fiber optic network is costly and difficult. The emerging 5G technology has been piloted in power distribution networks, though the cost-effectiveness of its large-scale deployment remains unclear. This paper proposes an economic evaluation method for 5G planning in power distribution networks, considering the coupling relationship between power distribution and communication networks and the identification of important network nodes. First, the objective function to solve the planned number of 5G base stations is established. This is solved using the adaptive particle swarm algorithm and K-means algorithm. Second, the coupling relationship between the distribution and communication networks is discussed and quantified. The node importance of the coupling network is analyzed to identify the important nodes, and micro base stations or optical fibers are added to improve the reliability of the distribution network at the communication level. Finally, an economic evaluation index of 5G planning of the distribution network is established. The paper compares the economic solutions of 5G and 4G communications in city and town scenarios using the IEEE 123-node network as an example, and concludes that the economics of 5G are better than those of 4G.

Abstract:The rapid development of cyber technology and the increase of flexible resources have transformed the distribution network into a cyber-physical distribution system, while the accompanying multidimensional uncertainties have brought new planning challenges. In this paper, an innovative approach is proposed to effectively leverage distributed resources while considering the impact of cyber-physical coupling in distribution network planning. A cyber-physical integrated planning model of the distribution network is proposed, considering the effects of spatial-temporal flexible resources and multi-network coupling. Specifically, a three-layer optimization model is established and analyzed by the simulate anneal-particle swarm optimization algorithm. The upper layer achieves the optimization of the location and configuration of energy storage systems and smart terminal units. The middle layer optimizes the data load migration strategy using spatial-temporal flexible resources to solve the voltage exceeding problem caused by high penetration of distributed power access, while the lower layer optimizes the cyber side communication topology, improving the convergence speed and control performance of the distribution network. Then, the optimization model is analyzed iteratively with objective functions including total planning cost, operation excess loss and distributed control performance. Finally, the effectiveness and economy of the proposed planning scheme is verified and compared to traditional methods.

Abstract:Monitoring various internal parameters plays a core role in ensuring the safety of lithium-ion batteries in power supply applications. It also influences the sustainability effect and online state of charge prediction. An improved multiple feature-electrochemical thermal coupling modeling method is proposed considering low-temperature performance degradation for the complete characteristic expression of multi-dimensional information. This is to obtain the parameter influence mechanism with a multi-variable coupling relationship. An optimized decoupled deviation strategy is constructed for accurate state of charge prediction with real-time correction of time-varying current and temperature effects. The innovative decoupling method is combined with the functional relationships of state of charge and open-circuit voltage to capture energy management effectively. Then, an adaptive equivalent-prediction model is constructed using the state-space equation and iterative feedback correction, making the proposed model adaptive to fractional calculation. The maximum state of charge estimation errors of the proposed method are 4.57% and 0.223% under the Beijing bus dynamic stress test and dynamic stress test conditions, respectively. The improved multiple feature-electrochemical thermal coupling modeling realizes the effective correction of the current and temperature variations with noise influencing coefficient, and provides an efficient state of charge prediction method adaptive to complex conditions.

Abstract:The increased deployment of renewable energy in existing power networks has jeopardized rotational inertia, resulting in system degradation and instability. To address the issue, this paper proposes a demand response strategy for ensuring the future reliability of the electrical power system. In addition, a modified fuzzy logic control topology-based two-degree-of-freedom (fractional order proportional integral)-tilt derivative controller is designed to regulate the frequency within a demand response framework of a hybrid two-area deregulated power system. The test system includes thermal power plants, renewable energy sources (such as wind, parabolic trough solar thermal plant, biogas), and electric vehicle assets. To adaptively tune the controller's coefficients, a quasi-opposition-based harris hawks optimization (QOHHO) algorithm is developed. The effectiveness of this algorithm is compared to other optimization algorithms, and the stability of the system is evaluated. The results demonstrate that the designed control algorithm significantly enhances system frequency stability in various scenarios, including uncertainties, physical constraints, and high penetration of renewables, compared to existing work. Additionally, an experimental assessment through OPAL-RT is conducted to verify the practicality of the proposed strategy, considering source and load intermittencies.