The 2017 edition of the China Renewable Energy Outlook (CREO 2017) shows that existing power plants can provide flexibility to the Chinese power system to ensure efficient integration of wind and solar power
In the past 10 years, China has invested massively in new renewable energy capacity and particularly wind and solar power have soared. Wind and solar power becomes more and more competitive compared with power from fossil fuels as the global trend of price reduction of the variable renewable energy (VRE) continues. China installed a record amount of 53 GW solar power in 2017 and continued the build-out of wind power. However, it has been difficult to integrate these highly fluctuating energy sources into the existing power system where coal-fired thermal power plants dominate. Consequently, VRE production has been curtailed especially in northern and western provinces in the level of 20-40% in the most affected provinces. This represents a direct economic loss to the Chinese society, unnecessary pollution from coal-fired power production and not least represents a barrier for a continued and increased growth of VRE in many provinces. Therefore, reducing curtailment is high on the political agenda of the Chinese government.
Power system flexibility a must
To avoid curtailment of VRE and ensure cost-efficient integration of VRE, the power system as such should be able to operate in a flexible way, adapting to both variation in the load and the variation in the production of wind and solar power. With rising share of VRE, system flexibility becomes ever more important. Today, the lack of flexibility in the power system is the major barrier hindering the full utilization of renewables. Many sources can contribute to increasing system flexibility including grid and market coupling, demand response, pump storage etc. However, enhanced flexibility of existing power plants has proven to be a cost-efficient source of flexibility in both Denmark and Germany.
The analyses in the CREO2017 show that flexible power plants also are cost-efficient sources of flexibility in China – particular at combined heat power (CHP) plants. A modest investment in retrofitting thermal power plants has a positive impact on not only overall system costs, but also VRE integration and reduced coal consumption. The 13th Five Year Plan for Power Sector Development not only targets reduction of VRE curtailment, but also aims at retrofitting 220 GW of existing coal-fired power plants in order to increase flexibility. A target of this magnitude is supported by the analysis results in CREO2017.
Today, a major barrier for power plant flexibility in China is the lack of incentives in the Chinese power system to drive the development. Hence, full integration of VRE requires institutional reform, including a power market reform establishing wholesale markets to facilitate more flexible power plants.
Market reform to incentivise flexible power plants
Economic incentives in competitive short-term wholesale power markets have been the main driver behind the development of thermal power plant flexibility in Denmark and Germany. It provides clear price signals for each hour of operation, which give the power plant owners reliable and shared information about the value of flexibility hour by hour. This gives them strong incentives to operate their plants more flexible and to make the adjustments on their plants, which are most profitable and thus generally most valuable for the power system.
Currently, China has eight pilot areas for establishing short term power markets. Success and experience from these pilot areas are important for establishing a national market in the future. A well-functioning short-term power market with reliable dynamic prices is fundamental for incentivising both cheapest sources of flexibility in general as well as incentivising the development of more flexible power plants. In this context, CREO 2017 analyses a number of measures for thermal power plants flexibility and assesses the implication of thermal power plants flexibility on system level through a comparison analysis. For more information, please see Part 3 of CREO 2017.
Author: Laust Riemann and Yuping Qiu