Capacity configuration optimization and analysis for multi-energy complementary microgrid in hydropower station considering the renewable energy accommodation

Aiming at the problems of large short-term fluctuation, strong randomness and difficulty to consume of renewable energy generation, it is an important way to integrate abundant wind and photovoltaic (PV) power into hydropower stations to promote the consumption of renewable energy sources (RES). A hydro-wind-PV and energy storage multi-energy complementary microgrid (MECM) model is proposed to meet the demand of load supply and RES consumption. Firstly, according to the characteristics of load and resource endowment, the MECM is established in a hydropower station. Secondly, according to the two different objectives of load self-sufficiency and RES consumption, the mathematical model for the capacity configuration optimization of MECM was proposed. Finally, combined with the practical case study, the effectiveness and practicability of this scheme are verified, and different configuration schemes are discussed based on different objectives.

Study on Frequency Regulation of Energy Storage for Hydropower Station

The paper firstly proposes energy storage frequency regulation for hydropower stations. Taking the actual operating hydropower station as an example, it analyzes the necessity of configuring energy storage to participate in frequency regulation for hydropower stations, and according to the hydropower station AGC regulate situation, the battery capacity of the energy storage frequency regulation system is designed, and the frequency regulation performance of the energy storage frequency regulation system at different battery capacities is analyzed. It provides reference for hydropower stations with similar needs.

Feasibility Analysis of Converting Hydropower Stations into Power Regulation Centers-Taking the Three Gorges Project for Example

In order to effectively respond to the global climate change and energy crisis, the structural transformation of energy has become an irreversible trend in the future development of China’s energy system. As a new kind of clean and renewable energy source, wind power technology has made great progress in recent years and has become relatively mature. The penetration rate of wind power in China’s power system increases continuously, playing an important role in promoting energy saving and emission reduction. However, because of their instability in time and space, wind power and solar power may pose great challenges to the safety of the power grid. To ensure power supply, thermal power generating units, combined with pumped-storage power stations, are still mainly used for peak load regulation nowadays, which is inconsistent with the long-term goal of carbon neutrality. This essay mainly studies the feasibility of turning hydropower stations into power regulation centers, taking the Three Gorges Project as the analysis object.

Runoff Prediction Model Based on Improved Convolutional Neural Network

Due to the influence of human regulation and storage factors, the runoff series monitored at the hydropower stations often show the characteristics of non-periodicity, which makes runoff prediction simulation difficult. This paper attempts to construct an improved one-dimensional convolutional neural network (CNN) model for runoff prediction simulation. The improved CNN model consists of two convolution layers and a full connection layer and uses LeakyRelu as the activation function. Based on the historical rainfall and runoff data of the ZheXi reservoir in Hunan Province, this paper uses the improved CNN model to simulate runoff prediction and compares the results with the traditional ANN model and the traditional CNN model. The results show that the improved CNN model is superior to the traditional ANN model and the traditional CNN model. It proves that the improved CNN model is suitable for the non-periodic runoff prediction simulation, and it can avoid the data problems such as gradient disappearance that may occur in the traditional neural network model.

Upper Limit and Power Generation Loss of Water Supplement from Cascade Hydropower Stations to Downstream Under Lancang-Mekong Cooperation

In cross-border water supplement cooperation, the supplement water discharged from upstream hydropower stations is the key to improving downstream benefits, but will lead to upstream power generation loss, so the upstream hydropower stations have to be aware of how much water they can offer and how much power they will lose to make the water supplement cooperation more reasonable. Therefore, this study puts forward a model to calculate the upper limit flow of water supplement of cascade hydropower stations under firm power constraints and water level constraints and proposes a new optimization method called the “collaborative-independent” joint optimization method to calculate the power generation loss under water supplement constraints. The results show that the upper limit flow will increase with the increase of annual inflow, and the uncertainty of the distribution of inflow in the year will also affect the upper limit flow: the larger the proportion of non-flood season inflow, the higher the upper limit flow. In normal and wet years, delaying water supplement time can significantly increase the upper limit flow by about 5% per month. Additionally, the “collaborative-independent” joint optimization method newly proposed in this paper can significantly improve the local optimization problem compared to the traditional optimization method. The power generation loss increases with the increase of water supplement flow, and delaying water supplement time can significantly reduce the power generation loss. The results of this paper can provide essential data support for future water resources cooperation negotiations in the Lancang-Mekong river basin to promote efficient and orderly water resources cooperation in the basin.

Impact and prospects of water conservation on fish habitat and advances of ecobiology operation in Yangtze River, China: A review

Yangtze River, the longest river in Asia, provides 40 percent of freshwater in China and plays an important role in ecological biodiversity. However, this ecosystem has been deteriorated by the continuously construction of reservoirs and hydropower stations. Many investigations have been carried for the biodiversity, hydrological indicators, and species distribution along Yangtze River caused by dam construction. As a result, the ecological operation has been gradually applied to mitigate the negative effects of water conservancy projects. In order to well know recent advances in the study of fish habitat in the Yangtze River Basin, 424 original papers published from 2000 to 2020 using bibliometrics were compiled in this research to analyze the developing trends including topics, data, and research status. The results of literature statistics showed that the related research fields on the effects of the reservoir on hydrological indicators mainly focused on negative impact caused by hydrological changes, water temperature effect, and sediment variation. In the studies on the habitats of fish, the four major Chinese carps and Chinese sturgeon were the main objects of concern, in which multi-objective joint operation, cascade reservoir operation, and model coupling have been widely adapted.