Optimal scheduling of wind–photovoltaic power-generation system based on a copula-based conditional value-at-risk model

In the context of the “dual carbon” goal, a high proportion of renewable energy connected to the grid to replace traditional high-carbon units has become a general trend. Taking the high proportion of renewable energy power system as the research object, the medium and long term planning of the installed capacity of source, grid, load and storage of power system is carried out considering the two dimensions of investment and operation maintenance, and the optimization model of source, grid, load and storage of power system is established. A low-carbon dispatching model considering carbon emission and demand response of distribution network is also proposed. Firstly, considering the characteristics of distribution network receiving power from the main network, the carbon emission model of distribution network based on carbon emission flow theory is constructed, and the low-carbon index of distribution network is proposed. Secondly, the improved dynamic carbon emission factor of distribution network is proposed, which is used as a guide signal to provide reference for low-carbon electricity consumption of distribution network users. According to the characteristics of users in the distribution network, the industrial demand response model aiming at low dispatch cost and low carbon and the residential demand response model aiming at electricity consumption satisfaction and low carbon satisfaction are constructed respectively.

With the interconnection of regional grids and the increasing penetration of renewable energy, the order of the power system model is getting higher and higher, which brings great challenges to the accuracy and real‐time performance of electromagnetic transient (EMT) simulation. The simulation of power systems with a high proportion of renewable energy requires a sharp increase in the performance of the hardware platform and the parallelism of the simulation algorithm. To solve this problem, the paper proposes a fine‐grained parallel modelling method for power systems with a high proportion of renewable energy, which is inspired by the latency insertion method used in the design of large‐scale integrated circuits. And this method is implemented on GPU to achieve the component‐level and device‐level parallelized simulation of power systems with a high proportion of renewable energy. Finally, the correctness of the proposed algorithm and the CPU‐GPU cooperative architecture is verified based on an improved 118‐bus case. The cascade system of the improved 9‐bus case is used as an example to verify the superiority of the proposed algorithm in terms of simulation efficiency.

response to the problems that the existing studies have not fully considered the role of hydrogen storage in the longtime and large-scale new energy consumption and the existing energy systems containing hydrogen storage have not fully considered the severe weather conditions in the scheduling, a medium-term and long-term optimal scheduling for community integrated energy system with high proportion of renewable energy and multi-type energy storage is proposed. Firstly, a typical day selection method and a typical day sequence formation method are proposed based on the traditional multi-scenario method and the year-round weather conditions; secondly, a medium-term and long-term operation state description method for hydrogen energy storage considering the internal characteristics of typical days and the external arrangement sequence of typical days is proposed; again, the architecture of the integrated energy system containing hydrogen and thermal energy storage is introduced. Based on the internal characteristics of a typical day and the external linkage of a typical day, a medium-term and long-term optimal scheduling model and solution method for the community integrated energy system with high proportion of renewable energy and multi-type energy storage are proposed. Finally, the effectiveness and practicality of the proposed method are verified through the analysis of calculation cases.

Wind power ultra-short-term prediction method based on NWP wind speed correction and double clustering division of transitional weather process

In recent years, with a rapid growth of the generation of hydropower, wind and solar power, renewable energy has occupied more than 60% of the total installed capacity of power grids in Qinghai, Yunnan, Sichuan, Tibet and other areas. Along with the yearly increased power transmission from these provinces, the ultra-high voltage AC/DC hybrid power grids will be evolving to be the multi-DC asynchronous grid, which is a trend of future represented by the work done in Yunnan. Taking Yunnan province as an example, this article studies the operational problems related to the multi-DC asynchronous power-sending grid with high proportion of renewable energy, and describes a new secure and stable operational technology that has been applied into the grid in Yunnan. We case-study the effects of the operation after the application of such technology and evaluate its practical influences.

Compared with other conventional energy sources, renewable energy, which results in less pollution and has numerous resources, is a significant factor in addressing the current issues of the serious environmental pollution and the resource depletion. Large-scale renewable energy connected to the grid could lead to a the change of the morphological structure and the operation modes of energy transmission. While current power grid evolution models did not consider the characteristics of renewable energy in the evolution strategy. The expansion mechanism of the future transmission network with a high proportion of renewable energy is studied in this paper. The operation cost including renewable energy curtailment are optimized using the production simulations, where the stochastic and intermittent of wind and solar energy are modeled. And the dual variable information is adopted to drive the grid upgrading. The expansion strategies for power grid of Zhejiang province in China are analyzed to balance the construction cost and curtailment cost of renewable energy.

With the development of power system with high proportion of renewable energy, large-scale wind power consumption has been in a tough situation in China. Recently, the transformation of "coal-to-electricity" has been promoted constantly in northern regions, and market trading mechanism of wind power for heating has been established and completed gradually, which has provided amount of absorption space for wind power. In order to make quantitative description of corresponding relationship between incremental wind power and incremental heating load, a calculation model for wind power consumed by electric heating load based on multi-state probability distribution is proposed in this paper. According to wind power output depicted by multiple probability distributions, we figure out both theoretical and practical wind power generating capacity with or without peak regulation constraints. On this basis, the contribution of heating load to reduce wind curtailment rate is obtained by comparing with consumption capacity before and after the load access to grid. Finally through a series of case study, it is proved that incremental electric heating load can indeed cut down wind curtailment of power system to some extent.

The integration of a high proportion of renewable energy has significantly reduced the grid inertia level and markedly increased the risk of transient frequency instability in power systems. Meanwhile, the large-scale integration of diverse heterogeneous resources-such as wind power, photovoltaics, energy storage, and high voltage direct current (HVDC) transmission systems-has considerably enriched the portfolio of frequency regulation assets in modern power grids. However, the marked disparities in the dynamic response characteristics and actuation speeds among these resources introduce significant nonlinearity and high-dimensional complexity into the system's transient frequency behavior. As a result, conventional methods face considerable challenges in achieving accurate and timely prediction of such responses. However, the substantial differences in the frequency regulation characteristics and response speeds of these resources have led to a highly nonlinear and high-dimensional complex transient frequency response process, which is difficult to accurately and rapidly predict using traditional methods. To address this challenge, this paper proposes an online prediction method for transient frequency response that deeply integrates physical principles with data-driven approaches. First, a frequency dynamic response analysis model incorporating the frequency regulation characteristics of multiple resource types is constructed based on the Single-Machine Equivalent (SME) method, which is used to extract key features of the post-fault transient frequency response. Subsequently, information entropy theory is introduced to quantify the informational contribution of each physical feature, enabling the adaptive weighted fusion of physical frequency response features and Wide-Area Measurement System (WAMS) data. Finally, a physics-guided machine learning framework is proposed, in which the weighted physical features and the complete frequency curve predicted by the physical model are jointly embedded into the prediction process. An MLP-GRU-Attention model is designed as the data-driven predictor for frequency response. A physical consistency constraint is incorporated into the loss function to ensure that predictions strictly adhere to physical laws, thereby enhancing the accuracy and reliability of the transient frequency prediction model. Case studies based on the modified IEEE 39-bus system demonstrate that the proposed method significantly outperforms traditional data-driven approaches in terms of prediction accuracy, generalization capability under small-sample conditions, and noise immunity. This provides a new avenue for online frequency security awareness in renewable-integrated power systems with multiple heterogeneous frequency regulation resources.

Refined production simulation and operation cost evaluation for power system with high proportion of renewable energy

In this paper, a rolling planning model for high proportion renewable energy generation power systems is proposed, considering frequency security constraints, to address the frequency stability challenges posed by increased integration of wind and solar energy into the power grid under the “double carbon” goal. First, this study establishes a frequency response model for a thermal generation unit (TGU) and analyzes the impact of the high proportion of renewable energy on system frequency stability. Subsequently, a dynamic frequency security constraint is formulated, which can be used in generation planning to address the frequency issues. Second, a bi-level rolling planning model for high proportion renewable energy generation power systems considering dynamic frequency security constraints is established. The upper level focuses on investment decisions. The lower level incorporates frequency security constraints into the operational simulation to guarantee the frequency stability of the power system when making decisions on the size of newly built TGUs annually. Finally, case studies are conducted to demonstrate the validity and effectiveness of the proposed rolling planning model.

As the increasing capacity of renewable energy sources (RESs), power system with high RES penetration urgently need virtual inertia support from RESs. Current research has found that, due to inherent time delay, providing excessive virtual inertia from RESs may instead cause small-signal instability in the power system. Therefore, determining the upper limit of virtual inertia from RESs is critical to ensuring small-signal stability. However, current studies have only proposed methods for determining small-signal stability in power systems that consider VIC time delay, with limited discussion of the upper limit of virtual inertia. Therefore, a discrete system frequency response (SFR) model considering VIC time delay is established in this paper. It is found through analysis that the frequency sampling period affects the critical stability condition much more sensitively than the time delay length. Furthermore, a sufficient condition for small-signal stability is proposed, which describes the upper limit of the virtual inertia of RESs by the frequency sampling period and the system inertia time constant. Although this condition is a conservative estimation of the upper limit of virtual inertia, but the experiment on the test bench of wind-integrated power systems verifies that the sufficient condition is close to the critical condition. The sufficient condition is independent of the time delay length, making it more suitable for guiding practical engineering applications.

The power generation of renewable energy sources is directly related to meteorological conditions like wind speed and sunlight. Integrating large-scale unstable power sources into the power system generates a need for adjustment and introduces operational risks. To improve the system’s adjustment performance and address the impact of uncertainties, this paper analyzes the operational characteristics and adjustment differences of various flexible resources and proposes a collaborative robust scheduling model for multi-flexible resources of source, grid, load, and storage, considering multiple uncertainties. The model aims to minimize system operation costs, including technical modifications, fuel consumption, start-up and shutdown, and energy curtailment, while satisfying constraints such as real-time supply-demand balance, system adjustment margin, and unit operation. An improved robust optimization theory is introduced to handle the uncertainties in renewable energy, transforming the model into an easier-to-solve problem. Finally, the case study results show that various flexible resources of source-grid-load-storage have different adjustment performances, and all types of resources are indispensable for a power system with a high proportion of renewable energy. Applying the proposed collaborative robust scheduling model can achieve a balanced decision-making process between risk and economy, ensuring complementary advantages and optimal allocation of various source-grid-loadstorage resources.

The high proportion of renewable energy into the power grid, say, the large-scale wind power generation connected to the power grid, is the key approach to achieve the clean and low-carbon energy transition. Under the premise of ensuring power grid's safe and stable operation, it is necessary to study the influence of wind power capacity expansion on the transient angle stability (TAS). Aiming at several typical dominant modes in Qinghai power system, which holds many new energy resources, the sensitivity of wind power capacity expansion in different locations to the TAS, as well as its key influence factors and feasible explanations, are explored. It may lay the foundation of the location optimization of wind power capacity expansion.

Solar ship, which integrates the solar photovoltaic (PV) system into its own ship power system, is becoming one kinds of most promising and fastest developing green ship. Since the electric energy transformed by PV system is provided to the power load through the ship's distribution system, the output power of synchronous generator will be reduced in proportion. Especially, if the matching relationship among solar PV system, energy storage system and the power load requirement is precisely analyzed and the operation characteristics and reliability of solar inverter have already meet the strict test standards for marine equipment, the design capacity of synchronous generators could also be reduced. The off-grid mode and grid mode are the main way of integrated application of solar power photovoltaic system of ship. And the solar PV system is a kind of inverter power supply, which is essentially based on the electronic inverted technology, so PV system can be regarded as a ‘fragile power source’ with ‘zero inertia’. Therefore, the influence of solar photovoltaic grid-connected system to the power flow and power quality of the ship power system cannot be ignored. And the effect of photovoltaic system on the power quality of transient and steady-state and flow calculation remains to be studied. This paper mainly research the changes of power load flow calculation(PLFC) on the system, using the toolbox PSAT of MATLAB Simulink. This paper research the PLFC on the system of different solar photovoltaic systems access points, and analysis the experimental results. The results show that, under the premise of the normal operation of the ship electric power system, the improvement of the capacity of solar photovoltaic system in ship , and different access modes of photovoltaic grid-connected system, have slight impact on the power flow of power system, indicating that the photovoltaic grid-connected system in ship is stable, an appropriate increase in the capacity of PV system is feasible. The results is of certain significance of secure application of grid connected photovoltaic system in this paper.

As the renewable energy generation continues to grow rapidly, the traditional power system is transitioning to a new power system with a high proportion of renewable energy. Consequently, the static voltage stability problem is becoming increasingly prominent. To address this issue, voltage support by the renewable energy generation is necessary. In this paper, we first analyze static voltage stability based on single source infinite system model. Then, we establish a simplified method to calculate the reactive power demand based on the short-circuit ratio. The method is further extended to multi-infeed renewable energy power systems using impedance matrix theory. Finally, we validate the effectiveness of the proposed method by simulating the IEEE 39 node system and a multi-infeed renewable energy power system.