[Objective] Inner Mongolia is actively promoting the development of clean energy heating to achieve environmentally friendly and sustainable winter heating goals. However, the uncertainty of wind and solar power output, coupled with fluctuations in heating demand driven by temperature variations, leads to supply -demand mismatches and challenges in power supply reliability and security. These issues have become critical bottlenecks restricting the development of clean energy heating. To enhance the economic viability and feasibility of clean 2 heating, this paper proposes an optimal dispatch method for a new energy heating system that integrates green power direct supply security constraints with the collaborative dynamic planning of supply, usage, and storage.
[Methods] First, the K-means clustering method is employed to consolidate historical data from the heating season in Inner Mongolia into four typical energy supply and demand scenarios, with the optimal number of clusters determined comprehensively using the elbow method and the Davies-Bouldin index. Second, constrained by voltage deviation, time-series power flow simulations are conducted to determine the hourly charging/discharging schemes for energy storage batteries, capacity configurations, and forecasted wind and PV output values under different scenarios. On this basis, leveraging the green power consumption strategy of the clean heating system, a multi-scenario integrated electricity and heat energy system is constructed. Electric boilers are select ed as the core equipment for electro thermal conversion, primarily powered by supporting wind and PV stations, with gas boilers configured as a backup heat source. Finally, using the distribution network simulation results as boundary conditions, an econom ic optimization dispatch model is solved, aiming to minimize operational and environmental costs.
[Results] A case study validates the feasibility and effectiveness of the proposed collaborative heating optimization model, which integrates time -series simu lation with economic dispatch. For a high -proportion new energy system with a penetration rate of 134%, and under the established grid structure and energy flow direction, the model achieves optimized electrochemical energy storage configuration and refine d collaborative operation of electro -thermal equipment. A multi-scenario energy storage configuration scheme and operation strategy are proposed, with storage capacity accounting for 10.88% to 43.52% of the installed capacity of the wind and PV stations. Ultimately, a safe and stable heating strategy based on an unstable power supply is formulated.
[Conclusion] The proposed method can effectively suppress voltage violations, reduce voltage fluctuations, and replace traditional CHP units with a combination of "wind power/photovoltaics, electric heating, and electro-thermal hybrid storage." This significantly enhances renewable energy consumption capacity, voltage stability control, and the system's economic and environmentally friendly operational performance.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |