Recently, the team of Professor Zhang Xiliang and Associate Professor Zhang Da of the Institute of Nuclear Energy and New Energy Technology of Tsinghua University and the team of Professor Lu Xi of the School of Environment of Tsinghua University joined the team of Michael Davidson of the University of California, San Diego (UCSD).The team of Assistant Professor D**IDSON and the team of Academician Zhang Xiaoyao of the Chinese Academy of Meteorological Sciences developed a renewable energy siting and power-system optimization model (respo) with high spatiotemporal accuracy, and used the model to study the optimization of renewable energy development layout under China's long-term carbon neutrality goal in the future.
The results of the analysis show that the electricity demand in China in 2060 is 15Under the assumption of 4 trillion kWh, China needs to deploy 2 billion 4 billion kilowatts of wind power and photovoltaic installed capacity respectively, and at the same time, attention should be paid to the development of energy storage systems and the expansion of UHV inter-provincial transmission networks.
The development of renewable energy, represented by wind power and photovoltaic power generation, is an important way to promote the low-carbon transformation of China's power system and achieve the goal of carbon neutrality. To build a power system with a high proportion of renewable energy, it is necessary to comprehensively consider factors such as wind and solar resources, geographical characteristics, land use, and grid absorption capacity for resource allocation.
For a long time, due to the fact that improving the spatiotemporal resolution will increase the complexity of the power system optimization model and bring difficulties to solve it, the power system capacity expansion and operation optimization model for the development of renewable energy in China has limited accuracy in spatiotemporal resolution, and it is difficult to fully describe the heterogeneity of renewable energy power generation in time and space.
To this end, the joint research team developed the respo model, which for the first time realized the power system optimization model to optimize the expansion and operation scheduling of renewable energy capacity at a large regional scale (Chinese mainland) at both the grid point (about 31km 25km) and the hourly level of 8760 hours a year.
The research team used the respo model to optimize the development layout of renewable energy under China's long-term carbon neutrality goal in the future, and designed 34 sets of scenarios covering different wind power and photovoltaic investment costs, energy storage construction costs, inter-provincial transmission line construction costs, thermal power generation flexibility, power system negative emission targets, land use policy strictness, and model spatiotemporal resolution assumptions for analysis and comparison. The results of the baseline scenario show that China's electricity demand in 2060 is 15Under the assumption of 4 trillion kWh, China needs to deploy 2 billion 4 billion kilowatts of wind power and photovoltaic capacity respectively, of which 80% of the photovoltaic installed capacity and 55% of the installed wind power capacity are concentrated within 100 kilometers of the power load center (Figure 1).
Figure 1Optimization results of wind power and photovoltaic layout of the RESPO model in the context of carbon neutrality in 2060, (a) and (b): installed capacity of grid-level wind power and PV; (c) and (d): Installed capacity of wind and photovoltaic power connected to each load center; (e) and (f): distance from the connected load center - cumulative distribution of wind power and photovoltaic installed capacity.
In addition, the development of energy storage systems and the expansion of UHV inter-provincial transmission networks are important development directions to improve the renewable energy consumption and security supply capacity of the power system. The results of the baseline scenario show that in order to ensure the consumption of about 6 billion kilowatts of wind and solar, more than 500 million kilowatts of pumped storage and more than 700 million kilowatts of electrochemical energy storage capacity need to be built. When the model is allowed to consider the deployment of long-term energy storage technologies represented by compressed air energy storage (20-hour discharge capacity) and flow batteries (10-hour discharge capacity), the installed capacity of long-term energy storage could reach a scale of 300 million kilowatts.
Figure 2Installed capacity of energy storage under different scenarios.
The results of the study's baseline scenario also show that interprovincial transmission capacity in 2060 will increase by about three times to 2020 levels. Among them, the regional line with the largest expansion is Mengxi-Shandong (increased from about 10 million kilowatts to 90 million kilowatts); Some other important north-south power transmission corridors also need to be further strengthened, such as Fujian-Zhejiang, which needs to add about 70 million kilowatts of capacity to transport wind power from Fujian to Zhejiang. Figure 3 shows inter-provincial power transmission (sub-Fig. A1), total capacity (sub-Fig. B1), and new capacity (sub-Fig. C1) relative to 2020.
Figure 3Construction of UHV transmission network under the baseline scenario of 2060, (a): inter-provincial net electricity flow; (b): total inter-regional transmission capacity; (c): Create a new transmission capacity.
In order to evaluate the impact of the strictness of land use policy on the relevant results, three scenarios were designed for the buildable potential of wind power and centralized photovoltaics, namely high, medium and low, and a total of nine scenarios were formed3 3. The model results show that when the assumption of land available for centralized PV construction is more conservative, distributed PV will replace centralized PV installation to a certain extent. In provinces with high electricity demand and large agricultural industries, competition for land for energy and food is more pronounced, and some eastern provinces will use almost all of the land available for centralized PV construction. In contrast, different land-use assumptions have a limited impact on wind power installation results. Figure 5 shows the installed capacity (sub-figure a), average power supply cost (sub-figure b), installed wind and solar capacity (sub-figure c), regional installed capacity of sub-grid (sub-figure d), capacity of inter-provincial transmission channels (sub-figure e), and installed capacity of energy storage (sub-figure f) under different land use scenarios.
Figure 4The optimization results under different land use policy stringencies, (a): the optimal installed capacity of each power generation technology; (b): the composition of the average cost of electricity in the power system (excluding distribution); (c): Installed capacity of wind and photovoltaic power; (d): Installed capacity of wind and solar power in different regions; (e): transmission line capacity; (f): Installed energy storage capacity.
On February 26, the study, titled "spatially resolved land and grid model of carbon neutrality in China," was published in the Proceedings of the National Academy of Sciences (PNAS). Lu Xi and Michael R. Davidsond**idson) is the corresponding author, and Da Zhang and Xiliang Zhang are the first authors. The research was supported by the National Natural Science of China** and the Tsinghua University Original Exploration Program.
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