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With the rapid development of the power industry, the safe and stable operation of the power system has become an important basis for safeguarding economic and social development. In order to adapt to the trend of rapid growth of new energy sources and the demand for transformation and upgrading of the power industry, the capacity allocation scheme of the power system needs to be constantly optimized and adjusted. To address the development planning of new power systems, a new power system development planning model based on two-layer planning is constructed, taking into account the operational output results of various types of units and the interaction between the configuration schemes. Through the analysis of the evolution of the power system in a region in the next 15 years, the development pattern of the new power system in different stages under the high, medium, and low scenarios of new energy development is optimally calculated to guide the development of the power system. The results show that the model can provide a quantitative reference for decision-making on energy policies and power strategies in the medium and long term.

The evolution of power system is a dynamic and complex process. Whether the evolution of power system can adapt to the macro environment and develop with all subsystems within the system depends on the matching and integration development among different evolutionary subjects. Based on the dissipation theory and Brusselator model, this paper constructs an evolutionary synergy model of the power system, and quantitatively analyzes the evolutionary synergy relationship between the evolving subjects of the power system and the overall evolutionary process of the power system. Then, from the socio- technical system transformation theory, we analyze the evolutionary elements of macro-environmental level, meso-institutional level and micro-beneficial level in the process of system transformation in China and the interaction among them. Finally, by comparing the entropy changes of the evolutionary participant subjects and the overall power system at each stage, the endogenous mechanism of the power system, the external elements and their interactions on the system development are studied in order to reveal the evolutionary synergistic law of China's power system and make suggestions for the development of the new power system. [ABSTRACT FROM AUTHOR]

Many repeated manual feature adjustments and much heuristic parameter tuning are required during the debugging of machine learning (ML)-based transient stability assessment (TSA) of power systems. Furthermore, the results produced by ML-based TSA are often not explainable. This paper handles both the automation and interpretability issues of ML-based TSA. An automated machine learning (AutoML) scheme is proposed which consists of auto-feature selection, CatBoost, Bayesian optimization, and performance evaluation. CatBoost, as a new ensemble ML method, is implemented to achieve fast, scalable, and high performance for online TSA. To enable faster deployment and reduce the heavy dependence on human expertise, auto-feature selection and Bayesian optimization, respectively, are introduced to automatically determine the best input features and optimal hyperparameters. Furthermore, to help operators understand the prediction of stable/unstable TSA, an interpretability analysis based on the Shapley additive explanation (SHAP), is embedded into both offline and online phases of the AutoML framework. Test results on IEEE 39-bus system, IEEE 118-bus system, and a practical large-scale power system, demonstrate that the proposed approach achieves more accurate and certain appropriate trust solutions while saving a substantial amount of time in comparison to other methods. [ABSTRACT FROM AUTHOR]

The gradual expansion of power transmission networks leads to an increase in short-circuit current (SCC), which has an impact on the secure operation of transmission networks when the SCC exceeds the interrupting capacity of the circuit breakers. In this regard, optimal transmission switching (OTS) is proposed to reduce the short-circuit current while maximizing the loadability with respect to voltage stability. However, the OTS model is a complex combinatorial optimization problem with binary decision variables. To address this problem, this paper employs the deep Q-network (DQN)-based RL algorithm to solve the OTS problem. Case studies on the IEEE 30-bus system and 118-bus system are presented to demonstrate the effectiveness of the proposed method. The numerical results show that the DQN-based agent can select the effective branches at each step and reduce the SCC after implementing the OTS strategies. [ABSTRACT FROM AUTHOR]

Addressing the shortcomings of existing low-frequency oscillation research on electrified railways, which has mainly focused on single-type trains and lacks the accurate modeling of traction inverter systems, in this paper we modeled and analyzed low-frequency oscillations in an electrified railway passenger and freight mixed-operation vehicle–grid system. First, an equivalent model of the DC side of the traction inverter was established, with the inverter system being equivalent to the parallel connection of the load resistance and the current source, and the specific mathematical expression was determined and verified by impedance measurement. Secondly, based on the equivalent model of the DC side of the traction inverter, a small signal model of the vehicle–grid system under the mixed operating conditions of CRH5 and HXD2B considering the inverter system was established. The generalized Nyqusit criterion was used to study the low-frequency oscillation characteristics under mixed transportation conditions. The accuracy of the established model and the correctness of the theoretical analysis were verified based on Matlab/Simulink. Finally, using the dominant pole theory to analyze the low-frequency stability conditions, the relationship between the number of mixed trains and the minimum short-circuit ratio was obtained, and the simulation verification was carried out. [ABSTRACT FROM AUTHOR]

Hydropower engineering is one of the most developed renewable energy generation techniques, which is characterized by high development concentration, large dispatching scale, many power stations, and long transmission distance. However, the unbalanced distribution of hydropower resources and the difficulty of absorbing hydropower lead to a large amount of abandoned water, which causes a large number of economic losses and energy loss in China. The topological structure and principle of the multi‐agent energy system of hydropower, hydrogen storage, and fuel cell are introduced here. The key technologies of the multi‐agent energy system are introduced from three parts: hydrogen production method of electrolysis water, hydrogen storage method, and application aspect of power generation system of solid oxide fuel cell. The main research direction of realizing the multi‐agent energy system of hydroelectric power, hydrogen energy storage, and fuel cell in the future is put forward, which has enlightenment significance for the construction of new power system and the research of realizing the goal of carbon neutral. [ABSTRACT FROM AUTHOR]

An improved explicit estimation algorithm is proposed for reliability estimation of the distribution network. Firstly, hierarchical clustering is used to identify and cluster typical feeders based on the topology structure. Secondly, the explicit formula of reliability index under each typical feeder topology is derived by regression analysis, to establish the model for network reliability estimation. Numerical simulations show the suitability of the proposed method in obtaining accurate reliability index for diversified network topology. [ABSTRACT FROM AUTHOR]

Reliability enhancement is a major motivation for integrating electric and gas energy distribution systems. Compared with reliability assessment at the stage of planning, which emphasizes calculating the system annual average indices, the coupling of gas and electric energy flows contributes more to the operational reliability of the integrated system, especially during peak-load periods. In this paper, a method is proposed that assesses system outage risk in each time period by modeling the consequence of the worst N-1 fault in the integrated electric-gas system. In order to accurately model the load transfer process, a novel dynamic load restoration model is applied to minimize load loss of the system, where the fluctuation of multiple energy flows during fault clearing periods is considered. The effectiveness of the proposed approach is validated by performing case studies. [ABSTRACT FROM AUTHOR]

The active distribution network is a new solution to the flexible utilization of distributed energy resources to suit the characteristics of the distribution network. Advanced “active” network management is to coordinate “generation, network, load” optimization and achieve the right balance between operational expenditure (OPEX) and capital expenditure (CAPEX). To demonstrate the advancement from introducing an active distribution network, the key features of distribution network planning mainly including traditional models is first introduced. Extensive literature in generic planning is then summarized and categorized in terms of objective functions, system modeling, solution algorithms, and tools. This is followed by an extended review and in-depth discussion of concepts and representative topic developments in optimal active distribution network planning. In contrast to traditional planning, it takes into account the effects from a range of active network interventions that are exercised at differing time scales while capturing the intrinsically stochastic behavior of renewable generation or demand response to produce strategic plans that are robust against a highly uncertain energy future. Finally, a multi-dimensional framework for optimal active distribution network planning is proposed to overcome the limitations of the current state of the art, and the challenges in each stage are also highlighted. [ABSTRACT FROM AUTHOR]