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Analysis Model and Empirical Analysis of Power Grid Evolution Path Considering Multiple Interactive Developments
JI Jie, LU Zongxiang, LIANG Mingliang, LI Haibo, LI Fuqiang, JIANG Zongnan
Electric Power Construction ›› 2023, Vol. 44 ›› Issue (7) : 57-69.
PDF(11791 KB)
PDF(11791 KB)
Analysis Model and Empirical Analysis of Power Grid Evolution Path Considering Multiple Interactive Developments
Power grids in the future will evolve from a single mode driven by a load to a dual-driven mode of a power source and a load. Diversified and flexible resources are urgently required for multiple interactive developments to realize a scenario with a high proportion of renewable energy. The effective identification of evolution-driven paths and the comprehensive optimization of evolution paths have an important guiding significance for clarifying the development direction of future power grids and constructing specific implementation paths. This study analyzed the uncertainty faced by power grid evolution from the aspects of technological maturity, potential, and energy cost and proposed a method for generating massive evolution paths. Subsequently, a data-driven evolution path analysis method was proposed, including path dimensionality reduction and visualization, driving factor identification based on time-varying patterns, and optimal path proposal generation based on the Pareto frontier. Finally, the evolution path of a high-proportion renewable energy system was analyzed using North China as an example. The analysis results indicated that photovoltaics in North China will gradually surpass wind power to become the most important power generation resource in the future and that carbon emissions in 2060 will be 81% lower than those in 2030. The relative importance of each factor differed marginally. At the economic and environmental levels, the most important factor was the price of coal, while the maximum investable capacity of battery energy storage was the main factor at the technical level. Efforts should be made to reduce unit investment in renewable and battery energy storage and coal prices and increase the upper limit of battery energy storage allocation to achieve an evolutionary path that considers both low cost and low carbon emissions.
flexibility resources / evolution uncertainty / massive evolution paths / path visualization / driving factor identification / optimal path
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Based on the existing relevant technical system, coal-fired power units can be gradually transformed through the “three-step” carbon reduction strategy, that is, through technical carbon reduction (coal consumption reduction and deep peak shaving) to achieve low carbonization, through fuel decarburization to achieve zero carbonization, through flue gas decarburization to achieve negative carbonization. The strategy makes coal-fired power units have advantages of reliable, harmonic and stable, and solves the high carbon emissions of the units. As a kind of zero-carbon new energy, biomass thermal power can simultaneously solve the following two dilemmas: the wind and solar new energy power plus energy storage can’t really ensure the safety of power grid; the traditional coal power is stable and adjustable, but the carbon emission intensity is too high. Biomass thermal power has become the backbone of China’s future low-carbon power supply, and will make historical contributions to the early realization of a new power system with new energy as the main body. |
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Power systems are transitioning toward having high shares of variable renewable energy (VRE) with the help of flexibility resources. However, multiple flexibility resources on the generation, storage and demand sides introduce multiple technical and economic uncertainties, making the transition hard to predict. Moreover, the benefit of these resources in the transition is unclear. To fill these gaps, this paper proposes a data-driven approach to explore the transition to a high VRE share-oriented power system with multiple flexibility resources. This approach generates a wealth of possible transition paths under multiple uncertainties and then uses them to quantitatively analyze the transition. Specifically, the proposed method includes principal component analysis-based path visualization, multiple index-based transition milestone identification, cluster and distance calculation-based key influential factor identification, marginal index-based flexibility resource benefit comparison and Pareto frontier-based path recommendation. Case studies based on the Northwest China power system, which involves wind, photovoltaics and concentrated solar plants, validate the effectiveness of the proposed approach and further indicate that flexibility resources increase rapidly with the growth of the VRE share. Of the multiple flexibility resources, storage contributes the most. Key influential factors include the capital cost of VRE and storage along with coal price. These factors should be the focus in a low-cost and low-carbon transition.
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本文中实验方案的制定和实验数据的测量记录工作是在清华四川能源互联网研究院等工作人员的大力支持下完成的,在此向他们表示衷心的感谢。
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