A Copula-Hammersley approach for probabilistic analysis of integrated power and heat networks

As the interaction between the electrical and district heating networks have been increased due to the wide utilization of combined heat and power units, the interest in providing an appropriate tool to analyze these integrated systems dramatically grows. Besides, the installation of renewable energy power plants, such as wind turbines, is increased because of their clean power generation. However, the amount of their generated power is uncertain since wind speed is not exactly determined. In this regard, deterministic approaches cannot be employed to solve the power flow problem, and it is necessary to use a probabilistic viewpoint. This paper presents a probabilistic power flow framework for the integrated power and heat networks based on a novel Copula-Hammersley technique. The proposed method is able to consider various system uncertainties along with the existed interaction between the heat and power networks to successfully solve the power flow problem. Simulations on a case study of Barry Island networks demonstrate the applicability and effectiveness of the proposed methodology. The superiority of this technique is verified by studying various indices and characteristics of the obtained results in comparison with some other conventional approaches. It is verified that the proposed technique reduces the average mean and standard deviation errors by approximately 45% and 72% compared to traditional methods, respectively. Furthermore, the efficiency ratio of the proposed approach is 15% higher than that of the conventional methods which shows that it is faster and more accurate than those techniques.