I. INTRODUCTION

II. SYSTEM MODELING

III. UNCERTAINTY IN MULTI-ENERGY FLOW PROBLEM

IV. HYBRID POSSIBILISTIC-PROBABILISTIC UNCERTAINTY ALGORITHM

V. CASE STUDIES

VI. CONCLUSION

REFERENCES

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 α-cut method is firstly implemented in processing fuzzy energy flow, which can reduce overestimation compared with the sole α-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.

INTRODUCTION

Currently, 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. Meanwhile, Renewable Energy Resources (RESs), such as wind power and photovoltaics, predominate in the sustainable transformation of energy systems, which also devotes to establishing complementary utilization of multiple energy carriers [1], [2]. In the numerous investigation about MEC systems, the uncertainty assessment is a critical issue. As there are various uncertainties (e,g., the variability and intermittency of the RESs [3], [4], stochastic fluctuations in energy loads [5]) in MEC systems, a reasonable tool to evaluate the uncertainties is indispensable to quantify and control the operational and planning risks of MEC systems. Deterministic energy flow calculation provides available measures for uncertain energy flow calculation, and it lays the foundation for planning analysis and optimal operation of MEC systems. The steady-state energy flow of electrical, gas and heat network is firstly investigated on the basis of Newton-Raphson technique considering interactions among different networks [6]. Due to the sensitivity of Newton method to initial guesses, a fast decomposing strategy is proposed to solve energy flow in large scale MEC systems [7].