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The large-scale centralized development of wind and PV power resources is the key to China's dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh. [ABSTRACT FROM AUTHOR]

Due to the lack of historical output data of new wind farms, there are difficulties in the scheduling and planning of power grid and wind power output scenario generation. The randomness and uncertainty of meteorological factors lead to the results of traditional scenario generation methods not having the ability to accurately reflect their uncertainty. This article proposes a RAC-GAN-based scenario generation method for a new wind farm output. First, the Pearson coefficient is adopted in this method to screen the meteorological factors and obtain the ones that have larger impact on wind power output; Second, based on the obtained meteorological factors, the Grey Relation Analysis (GRA) is used to analyze the meteorological correlation between multiple wind farms with sufficient output data and new wind farms (target power stations), so that the wind farm with high meteorological correlation is selected as the source power station. Then, the K-means method is adopted to cluster the meteorological data of the source power station, thus generating the target power station scenario in which the cluster information serves as the label of the robust auxiliary classifier generative adversarial network (RAC-GAN) model and the output data of the source power station is considered as the basis. Finally, the actual wind farm output and meteorological data of a region in northeast China are employed for arithmetic analysis to verify the effectiveness of the proposed method. It is proved that the proposed method can effectively reflect the characteristics of wind power output and solve the problem of insufficient historical data of new wind farm output. [ABSTRACT FROM AUTHOR]

Sustainable energy sources, such as wind energy, are pivotal in driving our energy landscape towards a more environmentally conscious and responsible future. Wind power, as an exemplar of clean and renewable energy solutions, adeptly harnesses the kinetic energy of the wind to generate electricity. While wind energy significantly contributes to our sustainability objectives, the quality of the energy it produces is equally essential. A critical challenge in this context is harmonic distortion, which manifests as unwanted fluctuations in the frequency and amplitude of electrical waveforms. Effectively mitigating these distortions within wind energy systems is vital to maintaining the stability and reliability of power grids, guaranteeing that the electricity supplied adheres to high-quality standards. The objective of this study was to conduct a technological prospection focused on the contemporary scenario of genetic algorithm applications in addressing harmonic variations. This investigation unearthed a total of 634 relevant documents. The findings suggest that the utilization of genetic algorithms for enhancing energy quality is a relatively recent but promising field. The State Grid Corp of China emerged as the principal contributor, with ten noteworthy inventors identified. Remarkably, both China and the United States lead in patent filings. The insights gleaned from these documents underscore the potential for further exploration and the synergistic application of these techniques. These collaborative efforts have the potential to yield processes and devices that offer significant economic and environmental advantages for the energy industry, solidifying our commitment to a cleaner and more sustainable energy future. [ABSTRACT FROM AUTHOR]

In China, with the increasing permeability of wind power, the power supply capacity is enough overall, but has shortage in partial-time. During peak hours, the capability of wind power consumption is poor and the power balance becomes more difficult. In order to maximize the utilization of wind power, the net loads are chosen as the response objectives, which contain significant uncertainties and have no probabilistic distribution characteristics. Under the traditional day-ahead power dispatch mode with fixed length time intervals and in the regions with insufficient hydroelectricity, the thermal generators take charge of the peak-load shaving. The frequent adjustments of thermal power output affect the system operation safety, economic benefits, and environmental benefits. Thus, a time-interval-varying optimal power dispatch strategy based on net load time-series characteristics is proposed in this paper. The net loads respond differently to intervals. The length of each time interval is determined based on the net load time-series characteristics analyzed by random matrix theory. The dispatch mode in each time interval is determined according to the characteristic quantification index calculated by the empirical modal decomposition and sample entropy. The proposed strategy and method can extend the continuous and stable operation time of the thermal generators, reduce the coal consumption caused by the ramping operation, and improve the safety, stability, and economy of the system. Furthermore, the proposed dispatch mode is environmentally friendly with reduced environmental cost and increased carbon credits. An actual provincial power grid in northeast China is taken as the example to verify the rationality and effectiveness of the proposed method and strategy. [ABSTRACT FROM AUTHOR]

In order to satisfy the strategic needs of energy sustainable development, renewable energy has developed rapidly and the power systems have been transformed to a new generation of power systems. In the renewable energy power generation technologies, the fastest developing wind power generation are highly intermittent and fluctuating. When high penetration of renewable power connects to the power grid and participates in the system dispatch, there will be more difficulties and challenges in the energy balance control. In this paper, a wind-thermal-nuclear-storage combined time division power dispatch strategy based on numerical characteristics of net load is proposed, where a specific thermal generating mode and an unconventional nuclear generating mode are discussed. In the strategy, the dispatch time division method is introduced in detail and the sample entropy theory is used to calculate the net load complexity. An adaptive thermal generating mode is determined according to the numerical characteristics of the net load. The nuclear generating modes of constant power operation, time division operation, and net load tracking time division operation are compared and analyzed, respectively. Finally, the wind-thermal-nuclear-storage combined time division power dispatch strategy aiming at decreasing the ramping power of thermal generators is achieved, and the increasing of the participation of pumped storage and improving of the continuous and steady operation time of thermal generators are realized. The experiment simulation is developed on an actual provincial power system in the northeast of China. The results verify that the thermal generator ramping power in the case based on SampEn are reduced, and the participation of pumped storage is improved. When both of the thermal generating mode and nuclear generating mode are according to the changing of net loads, the ramping powers of thermal generators are further decreased. [ABSTRACT FROM AUTHOR]

The quantitative evaluation of cluster wind power output volatility and source-load timing matching is vital to the planning and operation of the future power system dominated by new energy. However, the existing volatility evaluation methods of cluster wind power output do not fully consider timing volatility, or are not suitable for small sample data scenarios. Meanwhile, the existing source-load timing matching evaluation indicator ignores the impact of wind power permeability on the timing matching degree between wind power output and load. Therefore, the authors propose quantitative evaluation methods of cluster wind power output volatility and source-load timing matching in regional power grid. Firstly, the volatility-based smoothing coefficient is defined to quantitatively evaluate the smoothing effect of wind-farm cluster power output. Then, the source-load timing matching coefficient considering wind power permeability is proposed to quantitatively evaluate the timing matching degree of regional wind power output and load, and the corresponding function model of volatility-based smoothing coefficient and source-load timing matching coefficient is established. Finally, the validity and applicability of the proposed methods are verified by MATLAB software based on the actual power output of 10 wind farms and actual grid load in a certain grid dispatching cross-section of northeast China. The results demonstrated that the proposed volatility-based smoothing coefficient can accurately represent the smoothing effect of wind farm cluster power output while maintaining the volatility continuity of wind power output time series and without affect from the data sample size. The source-load timing matching coefficient can accurately characterize the difference in the timing matching degree between wind power output and grid load under different wind power permeability and the influence degree on grid load. [ABSTRACT FROM AUTHOR]

Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve accurate prediction of wind power generation in China, a hybrid prediction model based on the combination of Wavelet Decomposition (WD) and Long Short-Term Memory neural network (LSTM) is constructed. Firstly, the nonstationary time series is decomposed into multidimensional components by WD, which can effectively reduce the volatility of the original time series and make them more stable and predictable. Then, the components of the original time series after WD are used as input variables of LSTM to predict the national wind power generation. Forty points were used, 80% as training samples and 20% as testing samples. The experimental results show that the MAPE of WD-LSTM is 5.831, performing better than other models in predicting wind power generation in China. In addition, the WD-LSTM model was used to predict the wind power generation in China under different development trends in the next two years. [ABSTRACT FROM AUTHOR]

Accompanying the continuous increase in wind power penetration, the power system inertia is reduced, and the system frequency regulation performance deteriorates. Wind turbine generators are required to participate in primary frequency regulation (PFR) to support system frequency. Here, the PFR capability of the widely-used doubly-fed induction generator (DFIG) is evaluated to estimate the participation of the DFIG in system frequency control. The frequency regulation model of the DFIG is established and briefly discussed. The equivalent PFR droop coefficient is then deduced from the model using a small signal increment method to evaluate the DFIG's PFR capability. Key factors affecting the equivalent droop coefficient are studied, and the droop control is optimized to keep the equivalent droop coefficient in the desired range. The proposed method is verified utilizing a provincial power grid model of China. [ABSTRACT FROM AUTHOR]

Coal-fired power generation will dominate the electricity supply in China in the foreseeable future. Coal fired power units can play a crucial role in integrating intermittent wind energy and improving the overall energy efficiency of the power system. The integration benefits of wind power, along with the gains of high load rates of coal fired units, should be fully taken into account. An optimal model combining wind power and coal fired units is built to analyze the operational flexibility of coal fired units and the integration of wind power. Taking the coal fired units in North China Power Grid as an example, the dispatch costs and benefits are examined under the energy efficiency dispatch mode, in comparison with those under the fair dispatch rules and the installed capacity. The results show that increasing the flexibility of the power system under the energy efficiency dispatch mode may be the best choice for the power system with the high share of coal fired units to integrate more wind power, and that the units delivering flexibility services are financially influenced. The results also indicate that a certain amount of wind power curtailment may be reasonable, and that rational penalty rate and fees for the curtailment of wind power may help to optimize the operation of the power system and integrate more wind power. Based on these results, policy and strategy recommendations are proposed to promote the flexibility of coal fired units and change their operation mode and their dispatch mode in the power system. [ABSTRACT FROM AUTHOR]