Optimal real-time power dispatch of power grid with wind energy forecasting under extreme weather

With breakthroughs in the power electronics industry, the stability and rapid power regulation of wind power generation have been improved. Its power generation technology is becoming more and more mature. However, there are still weaknesses in the operation and control of power systems under the influence of extreme weather events, especially in real-time power dispatch. To optimally distribute the power of the regulation resources in a more stable manner, a wind energy forecasting-based power dispatch model with time-control intervals optimization is proposed. In this model, the outage of the wind energy under extreme weather is analyzed by an autoregressive integrated moving average model (ARIMA). Additionally, the other regulation resources are used to balance the corresponding wind power drop and power mismatch. Meanwhile, an algorithm names weighted mean of vectors (INFO) is employed to solve the real-time power dispatch and minimize the power deviation between the power command and real output. Lastly, the performance of the proposed optimal real-time power dispatch is executed in a simulation model with ten regulation resources. The simulation tests show that the combination of ARIMA and INFO can effectively improve the power control performance of the PD-WEF system

A Hybrid Algorithm for Short-Term Wind Power Prediction

Accurate and effective wind power prediction plays an important role in wind power generation, distribution, and management. Inthis paper, a hybrid algorithm based on gradient descent and meta-heuristic optimization is designed to improve the accuracy of prediction and reduce the computational burden. The hybrid algorithm includes three steps: in the first step, we use the gradient descent algorithm to get the initial parameters. Secondly, we input the initial parameters into the meta-heuristic optimization algorithm to search for the “best parameters” (high-quality inferior solutions). Finally, we input optimized parameters into the RMSProp optimization algorithm and conduct gradient descent again to find a better solution. We used 2021 wind power data from Guangxi, China for the experiment. The results show that the hybrid prediction algorithm has better performance than the traditional Back Propagation (BP) in accuracy, stability, and efficiency

A Hybrid Algorithm for Short-Term Wind Power Prediction

Accurate and effective wind power prediction plays an important role in wind power generation, distribution, and management. Inthis paper, a hybrid algorithm based on gradient descent and meta-heuristic optimization is designed to improve the accuracy of prediction and reduce the computational burden. The hybrid algorithm includes three steps: in the first step, we use the gradient descent algorithm to get the initial parameters. Secondly, we input the initial parameters into the meta-heuristic optimization algorithm to search for the “best parameters” (high-quality inferior solutions). Finally, we input optimized parameters into the RMSProp optimization algorithm and conduct gradient descent again to find a better solution. We used 2021 wind power data from Guangxi, China for the experiment. The results show that the hybrid prediction algorithm has better performance than the traditional Back Propagation (BP) in accuracy, stability, and efficiency

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM) and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP), and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL), are still imperfect, which make it difficult for the active distribution network (ADN) to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified

Ultrasound-Assisted Extraction of Anthocyanins from <i>Malus</i> ‘Royalty’ Fruits: Optimization, Separation, and Antitumor Activity

Red Malus ‘Royalty’ fruits are rich in anthocyanins. This study aimed to obtain the optimal parameters for the extraction and separation of anthocyanins from Malus ‘Royalty’ fruits and to evaluate the inhibitory effect of the enriched anthocyanin fraction on gastric cancer cells. Ultrasonic-assisted extraction was used for the extraction of the anthocyanins of Malus ‘Royalty’ fruit, and the extraction results showed that the optimum parameters were an extraction temperature of 20 °C, a solid–liquid ratio of 1:6 (g/mL), ethanol and formic acid contents of 70% and 0.4%, respectively, an extraction time of 40 min, and an ultrasonic power of 300 W. The optimum extraction parameters to achieve the highest anthocyanin yield by a single-factor experiment coupled with response surface methodology were identified. The separation results showed that the AB-8 macroporous resin was a better purifying material, with 60% ethanol as an adsorbent, and the adsorption–desorption equilibrium times were 6 h and 1 h, respectively. Cyanidin-3-galactoside was the main body composition separation of anthocyanins by a high-performance liquid chromatography-diode array detector. The antitumor activity results showed that the anthocyanins of Malus ‘Royalty’ fruits have a significant inhibitory effect on the gastric cancer cell line BGC-803. The in vitro cell viability test of CCK-8 showed that the inhibitory effect on tumor cells was more significant with the increased anthocyanin concentration, with a half maximal inhibitory concentration (IC50) value of 105.5 μg/mL. The cell morphology was observed by an inverted microscope, and it was found that the backbone of BGC-803 treated with a high concentration of anthocyanins was disintegrated and the nucleoplasm was concentrated. The mechanism of apoptosis was analyzed by Western blotting, and the results showed that with increasing anthocyanin concentration in the medium, the expression levels of the proapoptotic proteins Bax and Bak increased, and the expression levels of the antiapoptotic proteins Bcl-2 and Bcl-xL decreased, which coordinated the regulation of cell apoptosis. This research suggests that the enriched anthocyanin fraction from Malus ‘Royalty’ fruits have potential antitumor and adjuvant therapeutic effects on gastric cancer

Coordinated optimization control strategy of hydropower and thermal power AGC units

With the rapid increase of penetration level of new energy power generation, the construction of auxiliary service market is facing new challenges. The stricter requirements of the power plant unit AGC are proposed by the power system. How to coordinate and control the output of hydropower and thermal power units to increase the use of hydropower while meeting the requirements of AGC regulation is a problem to be solved. Under the condition of interconnection of units in the whole network, an optimal control strategy for joint commissioning of hydropower and thermal power plants that meets the performance conditions of ‘two rules’ is proposed in this paper. The strategy establishes the connection between hydropower and thermal power units. Combined with the output characteristics and economic characteristics of hydropower units and thermal power units, a coordinated optimization control strategy model of hydropower and thermal power AGC units suitable for the ’two rules’ assessment rules is proposed for each objective and constraint condition in the joint scheduling of hydropower and thermal power. The optimal mathematical model with multiple objectives is constructed to realize the distribution of AGC among different types of power plants and units, which can give full play to the regulation ability of hydropower and thermal power. The proposed strategy achieves the efficient use of clean energy and reduces the grid’s overall operating costs to achieve energy conservation and emission reduction. Simulation results verify the superiority of the proposed strategy