Hybrid Possibilistic-Probabilistic Energy Flow Assessment for Multi-Energy Carrier Systems

Qianyu Dong,Qiuye Sun,Chong Cheng,Zhibo Li,Yujia Huang

doi:10.1109/access.2019.2943998

Abstract

The uncertainty is a pivotal problem in Multi-Energy Carrier (MEC) systems, which leads to the strong demand of reasonable tools to evaluate uncertainties. When both possibilistic and probabilistic uncertainties exist in the real MEC systems, traditional possibilistic or probabilistic methods are no more suitable to be applied. Therefore, this paper proposes a hybrid possibilistic-probabilistic energy flow assessment method to evaluate these uncertainties. Firstly, to build a more precise uncertain model, the probabilistic and possibilistic uncertainties are respectively modeled by considering different uncertainties of sources, networks and loads of MEC systems, and the correlations among wind generation and energy loads. Then, the product t-norms of the extension principle plus $\alpha $ -cut method is firstly implemented in processing fuzzy energy flow, which can reduce overestimation compared with the sole $\alpha $ -cut method. Next, on the basis of Dempster-Shafer evidence theory, the hybrid possibilistic-probabilistic energy flow assessment approach is presented. Finally, two cases are carried out to verify the effectiveness and practicability of the proposed method.

Highlights

With increasingly global energy crisis and intricate interactions among electricity, gas and heat networks, the development of Multi-Energy Carrier (MEC) systems draws extensive attention worldwide
The uncertain energy flow calculation, which is based on steady-state energy flow, is regarded as an efficient tool to deal with uncertainties in MEC systems by offering more useful information for decision-making and planning as well
Due to the computational burden of Monte Carlo Simulation (MCS) method, and simplification of problem by mathematical assumption of analytical methods, the Point Estimate Method (PEM) in approximate methods is applied to investigate probabilistic energy flow to overcame uncertainties regarding the operation of MEC systems [10], [11]

Summary

INTRODUCTION

With increasingly global energy crisis and intricate interactions among electricity, gas and heat networks, the development of Multi-Energy Carrier (MEC) systems draws extensive attention worldwide. Due to the computational burden of MCS method, and simplification of problem by mathematical assumption of analytical methods, the Point Estimate Method (PEM) in approximate methods is applied to investigate probabilistic energy flow to overcame uncertainties regarding the operation of MEC systems [10], [11] Both uncertainties of RESs and loads correlation are left out of consideration in the corresponding researches of probabilistic energy flow calculation. To solve the above problems, the main contribution of this paper can be summarized: 1) A hybrid possibilistic-probabilistic multi-energy flow (HPPMEF) assessment approach is presented to evaluate uncertainty for analyzing security and assessing risk of MEC systems, which comprises of electricity, natural gas and heating sub-network. 2) A more accurate uncertain model is established for the MEC systems by considering the uncertainties of RESs generation, various energy loads, parameters of pipelines in gas and heating network, and related parameters of interdependencies from the perspective of the structure ‘‘sourcenetwork-load’’. Where L represents electrical loads or gas loads or heat loads in different sub-network; σ and μ are mean and standard deviation of corresponding energy loads

POSSIBILISTIC UNCERTAINTY MODELING

POSSIBILITY THEORY

CASE 1

Findings

CONCLUSION