Interval Energy Flow Analysis in Integrated Electrical and Natural-Gas Systems Considering Uncertainties

Abstract

As integrated electrical and natural-gas systems (IENGS) are popularized, the uncertainties brought by variation of electrical load, power generation, and gas load should not be ignored. The aim of this paper is to analyze the impact of those uncertain variables on the steady-state operation of the whole systems. In this paper, an interval energy flow model considering uncertainties was built based on the steady-state energy flow. Then, the Krawczyk-Moore interval iterative method was used to solve the proposed model. To obtain precise results of the interval model, interval addition and subtraction operations were performed by affine mathematics. The case study demonstrated the effectiveness of the proposed approach compared with Monte Carlo simulation. Impacts of uncertainties brought by the variation of electrical load, power generation, and gas load were analyzed, and the convergence of energy flow under different uncertainty levels of electrical load was studied. The results led to the conclusion that each kind of uncertainties would have an impact on the whole system. The proposed method could provide good insights into the operating of IENGS with those uncertainties. gas (P2G) and gas-fired power generation in the IENGS in Ref. [16]. Since the turboexpander is also commonly used to strongly link the electrical and gas networks, Ref. [17] investigates operational parameters of natural-gas regulation stations (GRS), which influence the efficiency of the gas expansion process and determine selection criteria for a cost-effective application of turboexpanders at selected GRS. The turboexpander has been combined in a CHP plant that supplies a district heating network, in order to save energy and reduce CO 2 emissions by means of smart systems integration in Ref. [18]. The steady-state energy flow considering time-scale characteristics has also been analyzed [19][20][21][22]. A multitemporal simulation model is presented to carry out integrated analysis of electricity, heat, and gas distribution networks, with specific applications to multivector district energy systems in Ref. [19]. A modified teaching-learning-based optimization algorithm is utilized to solve the multiperiod optimal energy flow of multicarrier energy networks in Ref. [20]. Ref.[21] proposes a quasi-steady multienergy flow model and calculates the energy flow of electricity and heating systems considering the time-scale characteristics. An integrated simulation model has been proposed considering the impacts of interdependencies between electricity and natural-gas systems in terms of security of energy supply in Ref. [22].However, the uncertainties of IENGS are not considered in the above references. There are some papers considering the effect of uncertainties and disturbances in Model Predictive Control (MPC) [23], DC microgrid [24], damping the power swings [25], and optimal power flow [26]. Actually, there exist some kinds of uncertain factors in the operating IENGS, such as power load, gas load, and power generation. A probabilistic energy...