Journal of Energy Engineering

This paper presents the application and design of a novel stochastic optimal control methodology based on the $Q$-learning method for solving the automatic generation control (AGC) under the new control performance standards (CPS) for the North American Electric Reliability Council (NERC). The aims of CPS are to relax the control constraint requirements of AGC plant regulation and enhance the frequency dispatch support effect from interconnected control areas. The NERC’s CPS-based AGC problem is a dynamic stochastic decision problem that can be modeled as a reinforcement learning (RL) problem based on the Markov decision process theory. In this paper, the $Q$-learning method is adopted as the RL core algorithm with CPS values regarded as the rewards from the interconnected power systems; the CPS control and relaxed control objectives are formulated as immediate reward functions by means of a linear weighted aggregative approach. By regulating a closed-loop CPS control rule to maximize the long-term discounted reward in the procedure of online learning, the optimal CPS control strategy can be gradually obtained. This paper also introduces a practical semisupervisory group prelearning method to improve the stability and convergence ability of $Q$-learning controllers during the prelearning process. Tests on the China Southern Power Grid demonstrate that the proposed control strategy can effectively enhance the robustness and relaxation property of AGC systems while CPS compliances are ensured.

As the energy supply shortage and environmental pollution have increasingly become the major obstacles to China’s economic development, the Chinese government has proposed various policies to reduce energy consumption, one of which is to implement a differentiated electric power price scheme (DEPP) on the energy-intensive industries (EIs). Although it is only imposed on EIs, its indirect impact on other sectors or national economy could be profound. This paper applies an input-output (IO) model, which composes 42 sectors calibrated with data in 2002 to examine the potential impact of DEPP. The results show that DEPP would result in significant energy savings at the expense of declines in gross domestic product (GDP) and increases in consumer price index (CPI). The ancillary benefits include reduction of emissions from the energy-intensive sector.

China has made great achievements in wind power generation. By the end of 2009, the installed capacity of wind power totaled 25.8053 GW, 13.8032 GW of which was added in 2009. Although the industry has developed at an impressive rate, its scale is still comparatively small, not fully matching the country’s economic size and great demand for green power. It is widely believed that the wind power market in China can develop at an even faster rate over the next decade. A stable market for wind power investment relies on both the cost of wind power and an effective pricing policy to motivate growth in the wind industry. This paper presents corresponding analysis of the costs of wind power generation and the current pricing policies implemented in China. The composition of wind power costs is elaborated through comparing it with that of conventional power resources. The localization of wind turbine manufacturing, which aims to decrease the wind generation costs and promote the development of the local wind power industry, is introduced. Two current pricing systems applied in China are examined: the price committed by the wind power concession bidding projects and the price authorized by the provincial governments. An inflation-adapted model is proposed to analyze the risk of concession prices. Finally, the paper concludes with discussions on the potential benefits and the future strategies for the development of wind power in China.

The Chinese government has set ambitious goals for nuclear power. By 2020, China must reach a 40-GW nuclear power generation capacity, have 18 GW of additional nuclear power capacity under construction, and ensure that approximately 4% of electricity generation (i.e., 260–280 billion kWh) comes from nuclear power. This paper provides an overview of nuclear power development in China and analyzes the roles of nuclear power manufacturers and investors. This paper further discusses current government policies, potential changes to current policy, the future of nuclear power, and the barriers to nuclear power development in China. The paper then summarizes the experiences of other countries with successful stories in developing nuclear power. Finally, recommendations for overcoming the various obstacles to nuclear power development in China are proposed, such as reforming the structure of China’s nuclear power industry, establishing an effective legal system for nuclear power safety, and improving China’s technology development.