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With the increasing installed capacity of renewable energy in the energy system, the uncertainty of renewable energy has an increasingly prominent impact on power system planning and operation. Renewable energy such as wind and solar energy is greatly affected by the external weather. How to use a reasonable method to describe the relationship between weather and renewable energy output, so as to measure the uncertainty of renewable energy more accurately, is an important problem. To solve this problem, this paper proposes a renewable energy scenario generation method based on a conditional generation countermeasure network and combination weighting method (CWM-CGAN). In this method, the combination of AHP and the entropy weight method is used to analyze the meteorological factors, the weather classification is defined as the condition label in the conditional generation countermeasure network, and the energy scenario is generated by the conditional generation confrontation network. In this paper, the proposed method is tested with actual PV data, and the results show that the proposed model can describe the uncertainty of PV more accurately. [ABSTRACT FROM AUTHOR]

The unit energy consumption and its price have become the main obstacles for the future development of the aluminum electrolysis industry in China. Meanwhile, wind power is widely being abandoned because of its instability. In this study, a novel idea for wind power accommodation is proposed to achieve a win-win situation: the idea is for nearby aluminum electrolysis plants to absorb the wind power. The features of the wind power distribution and aluminum electrolysis industry are first summarized, and the concept of wind power accommodation by the aluminum industry is introduced. Then, based on the characteristics of aluminum reduction cells, the key problems, including the bus-bar status, thermal balance, and magnetohydrodynamics instabilities, are analyzed. In addition, a whole accommodation implementation plan for wind power by aluminum reduction is introduced to explain the theoretical value of accommodation, evaluation of the reduction cells, and the industrial experiment scheme. A numerical simulation of a typical scenario proves that there is large accommodation potential for the aluminum reduction cells. Aluminum electrolysis can accommodate wind power and remain stable under the proper technique and accommodation scheme, which will provide promising benefits for the aluminum plant and the wind energy plant. [ABSTRACT FROM AUTHOR]

With the rapid growth of energy consumption, how to utilize energy in an efficient and cheap way becomes an intensive problem. This paper proposes an optimal operation strategy to reduce system fuel costs and increase system stability by independently considering cooling loads and adjusting CHP heat to power ratio seasonally. In this paper, a mathematical model of CHP operation is introduced to reveal the relationship between the supplementary volume of diesel oil and CHP heat to power ratio. Meanwhile, by analyzing the influence of seasonal factor on energy consumption, CHP heat to power ratio is optimized seasonally. Then, by independently considering the impacts of the cooling loads on system operation, the particle swarm optimization (PSO) algorithm is used to optimize the operation strategy of each device. Finally, this paper validates the positive effects of storage devices on improving system economy and stability under the premise of the time-of-use gas price. Results show that system fuel costs can be reduced by 5.2% if the seasonal factor is considered. Additionally, by optimizing the operation strategy, the peak valley gap of electrical loads in summer reduces by 40.7%. Moreover, the proposed strategy successfully utilizes storage capacity to shift loads and respond to gas price. [ABSTRACT FROM AUTHOR]