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With the goal of “double carbon,” wind power and PV are connected to the grid on a large scale, which poses a great challenge to the safe operation of the grid. The synergistic optimization of “hydro-wind-PV hybrid systems” can bring into play the ability of coordination and mutual assistance between different types of power sources, which is one of the important measures to increase the safe operation of the power grid and reduce abandoned wind and photovoltaic power. Based on the analysis of the characteristics of hydro-wind-PV power, the “hydro-wind-PV” integrated network-source cooperative optimization scheduling model is constructed to maximize the source-load matching and the consumption of clean energy. Finally, the results of a case study of a hydropower-wind power-photovoltaic cluster project in southwest China are used to verify the rationality and feasibility of the model.

This paper proposes an optimal generation scheduling approach based on linear relaxation and mixed integer programming, which is used to solve the generation dispatch problem. The quadratic transmission loss constraint of each transmission line is converted into linear constraints by using the linear relaxation and mixed integer programming technique. Consequently, the original optimal generation scheduling problem is formulated as a quadratic programming or mixed integer quadratic programming problem that can be solved by commercial optimization solver. In order to improve the efficiency of algorithm, this paper further analyses the generation scheduling model and deletes the redundant variables and constraints. Three test systems, including IEEE 30-node system, IEEE 118-node system, and Polish 2746-node system, are employed to examine the effectiveness of the proposed method. The comparative results obtained by the proposed method, quadratically constrained quadratic programming method (QCQP), and solving constraint integer programs solver (SCIP) verify the effectiveness of the proposed method in solving the optimal generation scheduling problem.

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.

This paper introduces the power generation principle of solid oxide fuel cell, analyzes the advantages and technical bottlenecks of solid oxide fuel cell power generation mode application, studies the market prospect of solid oxide fuel cell application, and explores the economy of solid oxide fuel cell. The role of solid oxide fuel cells in the process of 'carbon peak, carbon neutralization' is proposed, which mainly includes the decomposition of carbon dioxide and water vapor into carbon monoxide and hydrogen, the construction of power plants with solid oxide fuel cells to solve the problem of grid hollowing and energy storage, the introduction of renewable energy and the rapid reconstruction of disasters. The demonstration of a large-scale solid oxide fuel cell power station is introduced, which provides a technical scheme for achieving the goal of 'carbon peak and carbon neutralization'.

Today’s power systems are subject to various challenges arising from the large-scale integration of renewable energy sources (RES), especially wind energy production, which not only improves the economic efficiency of production capacity, but also brings higher demand for grid flexibility. At the same time, the process of electric power marketization has been promoted. The mechanism of ancillary services market, especially peak regulation market, has been increasingly sounder than before. In this paper, a power grid-generator collaborative expansion planning for the deep peak regulating market is proposed. The upper model is the planning layer model to determine the line to be selected and unit reconstruction. Based on the network frame of upper layer, a real time clearing model for peak regulation market is presented in lower layer, which pass the returns on investment to the planning model. Finally, a case analysis and numerical results show the effectiveness of the proposed planning and clearing model.

To settle the failure detection conundrum of the PEMFC power generation system, a failure detection approach of the PEMFC power generation system ground on local reservation projection (LLP) and learning vector quantization neural network (LVQNN) is devised. In this method, normalized preprocessing and LLP algorithms are used to shorten the dimensionality of the primary data, and the LVQNN is used to identify the pre-processed data. The results of 600 groups of fault data of the PEMFC water management subsystem reveal that the proposed approach can diagnose the faults of the PEMFC power generation system with 98.33% accuracy and can apply to the failure detection field of PEMFC power generation system.

Integration of distributed generation (DG) in distribution network changes the topological structure of distribution network. Meanwhile, the location and size of DG as well as the evolution of the topology structure of distribution network will affect the power supply reliability, which will make the planning process of the distribution network extremely complicated. For this, this paper presents a new distribution network planning model with reliability estimation method. The several network templates are obtained with the hierarchical clustering algorithm based on tree edit distance (TED), which could reduce the complexity of the distribution network. Then, the topology characteristics of the clustered network templates will be correlated with reliability index, which is formulated as explicit formulation. Similarly, the correlation model between the reliability index and DG planning is established through BP neural network. Furthermore, the distribution network planning model under each network template is aggregated, which contains the established reliability estimation model. Investment costs of distribution networks with different network templates are analyzed for different scenarios. The results suggest that unlike existing solution techniques for reliability correlated distribution network planning, the proposed method can effectively converge to the optimal solution, and evaluate the investment performance for large-scale distribution networks.

The rapid development of wind power generation imposes unprecedented challenges on power system operations due to stochastic variations. This paper seeks to compute how much nodal injected wind power variation a power system can handle. Two corrective control strategies—the fixed and the fully adaptive participation factor—are considered. To speed up the computation for fully adaptive participation factor strategy, a pairwise convex hull is proposed to build a more compact initial set, and a local admissible region is characterized instead of the whole region. To reduce the required computation, a novel method is proposed to decrease the number of inequalities. Finally, the effectiveness and efficiency of the proposed methodology are verified on a modified 5-bus and 118-bus systems.

Optimal planning of distributed generation (DG) in distribution networks is key for improving energy utilization efficiency and system operation benefits. Considering the uncertainties and temporal correlations of DG output and load demand, a multi-scenario chance-constrained economic model for DG planning is established in this paper. The model considers the comprehensive benefits of environmental, reliability and other aspects, as well as the active curtailment management of DGs. Thereafter, the model is extended to the coordinated planning of both DGs and tie lines, which is formulated as a multi-objective model. An improved genetic algorithm based solving strategy integrated with game multi-objective decision method is proposed. The feasibility and effectiveness of the proposed models are verified on the IEEE 33-bus distribution system. The impacts of natural resource distribution, confidence level, unit environmental cost and other parameters are investigated as well. The case studies also prove the integration of complementary DG generation could help improve the maximum capacity of DG and indicate the environmental benefit is the vital incentive to introduce DG into the distribution network.

Transmission grid planning under an electricity market with separated power generation, transmission, distribution and sale links, is facing more challenges, due to the market uncertainties. In this paper, based on marginal price, an optimal planning model of transmission grid considering power transaction is proposed to maximize congestion surplus. Adopting network voltage and investment budget constraints, dynamic differential evolution algorithm was used to figure out the model, yet, in lower rate of convergence. As a result, we combined the advantages of different iteration strategies, and proposed an improved dynamic differential evolution algorithm. In the simulations based on a west grid in China, algorithm convergence and validity are analyzed.

As enterprises, institutions, communities and households continue building distributed power sources, the application market for energy storage is expanding, which is driving the rapid development of energy storage technology. At the same time, due to the implementation of the new power system reform plan, the power grid will enter into a new era of power sales, the monopoly of the power grid is broken, and different power sellers continue to emerge, providing a unique opportunity for the development of energy storage. Firstly, the typical energy storage modes of multi-investors are analyzed to meet their satisfaction. Also, the energy storage benefits obtained by different investment entities are analyzed. Finally, based on the full life cycle cost of energy storage, the investment boundaries of different energy storage capacities are calculated. The simulation results validate the effectiveness of the proposed method.

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.

the paper investigates the potential for added value of the active filtering function of a STATCOM at the AC grid access point for the connection of wind power. This study is based on a realistic project with the network parameters and background harmonics required for modelling provided by the grid operators. The model is constructed in DIgSILENT PowerFactory. The phenomenon of background harmonic amplification is illustrated and two leading candidate switching scenarios are selected for the studies on low order harmonics. The active power filtering control algorithms for the grid connected STATCOM is evaluated in this study to provide a level of understanding of the potential limitations and problems that might be encountered in performing the APF function in STATCOM.

regarding the reliability assessment in the planning process of the medium-voltage distribution system, a novel reliability indices estimation method is proposed in this paper. It makes reliability indices can be expressed by explicit formula and considers different network topology. First, typical feeder structures are extracted in the candidate area using tree edit distance and hierarchical clustering algorithm. For each typical network structure, the reliability evaluation model is established. Influences of various factors on reliability indices including fault isolation, load restoration and reliability enhancement equipment are formulated by regressive analysis respectively. The feasibility and effectiveness of the reliability assessment algorithm are verified by the test cases. The results indicate that little data would be required to realize fast reliability indices calculation by the proposed algorithm. Besides, it can guarantee a high calculation accuracy dealing with various topology.

This paper proposes a voltage compensation scheme (VCS) to improve the commutation failure immunity (CFI) of line-commutated converter-based high voltage direct-current transmission (LCC-HVDC) systems with an unified power flow controller (UPFC). A voltage compensation control system was designed for the UPFC, which enables the UPFC to inject three-phase voltages in series with the receiving-end ac source to compensate the distortion and magnitude drop of the inverter-side ac voltage in the cases where external disturbances occur. In this way, satisfactory commutation voltage is provided for the inverter station of a LCC-HVDC system and CFI of the LCC-HVDC system is improved. Simulation studies were undertaken on the CIGRE LCC-HVDC benchmark system in the cases where single-phase-to-ground faults occurred in the receiving-end ac grid. CFI of the test system having the proposed VCS, a commutation failure prevention method (CFPREV), and a direct-current predictive control strategy (DCPC) implemented respectively was investigated.

The studies of the conventional optimal planning of AC/DC hybrid power system are barely concentrated on the VSC control strategies which can be very meaningful for system expansion. A load flow calculation of hybrid system integrated with VSC control strategy is proposed in this paper. Then based on the flow calculation, an optimal expansion planning with the key objective of economic efficiency is designed. The model of power flow for AC/DC power system is calculated by alternative algorithm and the objective function of the expansion planning is according to the cost minimization with the constraints of the costs for generation and the transmission lines. Solved by the calculation model and planning model, an example is presented in the final part of this paper to illustrate the influence of the control strategy of VSC on the power flow calculation as well as the optimal planning and indicate the value of the consideration of the converter control strategy in the optimal planning.

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 dif...

An online reliability evaluation method for distribution network considering time sequential load transfer procedure is presented in this paper. The method, which takes the medium voltage distribution feeder as the evaluation object, assesses the worst outage risk in real time under the extreme fault condition. In order to simulate the load restoration procedure after fault, an optimization model of the load transfer strategy is set up aiming at minimizing total energy loss. The power variation in load transfer periods as well as the continuous back-up power supply ability is considered in the model, and a multi period heuristic search algorithm is applied to solve it efficiently. The effectiveness and feasibility of the proposed method is verified by case study, and the results can provide references for distribution system operators in distribution network.

Urban grid system with high proportion of air conditioning load has the characteristics of unpredictability and uncontrollability. The sudden rise and drop of city load is becoming the norm. This has a negative impact on the system stability and the situation may get worse when fault occurs in such areas. The reinforcement of city network is restricted by high short-circuit current level and limited transmission corridors, thus the system operators seek more flexible and controllable operation methods. This paper analyses the application of VSC-HVDC technology in city center systems, focusing on providing flexible power support for the connected areas while improving the characteristics of air conditioning load. The effect of VSC-HVDC on the city center system voltage stability is revealed and the capability of MMC for voltage support at different operating conditions is discussed thoroughly.

In general the most highly developed urban distribution networks provide high levels of reliability. However, the majority urban distribution networks still face high levels of outage risk during peak-load periods, especially when the available back-up generation capacity is insufficient. In order to accurately assess the outage risk during such operational periods, four system outage risk evaluation indices are presented based on the impacts of the worst fault case in the medium voltage distribution feeder. As a consequence, in order to reduce the outage risk, a novel multiple time interval based demand transition optimization procedure is demonstrated in this paper. By considering the changes of load and backup generation output in the whole demand transition process, the continuity of restoration is guaranteed. The effectiveness of the proposed approach is validated by the case study.

This paper presents an investment funds allocation model for distribution system upgrade based on data-driven technique. First, a bilevel programming evaluation system is established, which takes upgrade measures as element layer indices and comprehensive evaluation parameters as performance layer indices. In order to mine the correlation between these indices, enormous indices data generated by a virtual distribution system program is analyzed through artificial neutral network (ANN). Second, the trained ANN is embedded in the distribution network upgrade optimization model, which is solved by genetic algorithm (GA). Finally, effectiveness and feasibility of model are verified by a city distribution system.