Regulation and optimization methodology for smart grid in Chinese electric grid operators using quality function deployment, equilibrium theory, fractal theory and mathematical programming

Abstract

As the world is increasingly dependent on energy for the economic and social development and China’s Total Net Electricity Generation （TNEG） has remained the highest since 1996 due to its rapid economic growth, it is important to closely examine the operations of China’s electric power market, particularly the State Grid Corporation of China (SGCC) since it is the largest Electric Power Grid Operator (EPGO) in both China and the world. This research has addressed the problem and the urgent needs for the development of a sound framework and methodology for the effective regulation and optimization of the operations and quality management of the SGCC. Based on the critical literature review, the aspects and steps of the solution to the problem have been progressively presented. Firstly, a Country Wealth (CW) curve has been developed to characterize electricity generation in terms of TNEG, with China’s unique position identified. Further, the data has clearly indicated that China’s TNEG has also been closely correlated with the economic growth and the carbon emissions during the 30 years period of 1980-2010. Secondly, compared with the Equilibrium Energy Regulation Model, there are clear deficiencies and problems with the current regulation of China’s electric power market. The improvements in the integration of regulation strategies and the formation of one single effective regulator have been identified and proposed. Thirdly, a uniform regulation structure and framework based on fractal theory and QFD (quality function deployment) has been developed to integrate the existing and future electric power strategies, including smart grid strategy and sustainable development strategy(etc.). Through the use of QFD, the EPGO (SGCC) functions and operations can be prioritized and appropriately designed. Finally, the QFD methodology has been extended to achieve the optimization of quality and service operations given the target cost of the business processes. The methodology can be applied to both business and technical processes of the EPGOs since quality may be interpreted as a total quality involving the needs and expectations of various customers or stakeholders.