Multi-Linear Probabilistic Energy Flow Analysis of Integrated Electrical and Natural-Gas Systems

The increasing interdependency of electricity and natural gas systems promotes coordination of the two systems for ensuring operational security and economics. This paper proposes a robust day-ahead scheduling model for the optimal coordinated operation of integrated energy systems while considering key uncertainties of the power system and natural gas system operation cost. Energy hub, with collocated gas-fired units, power-to-gas (PtG) facilities, and natural gas storages, is considered to store or convert one type of energy (i.e., electricity or natural gas) into the other form, which could analogously function as large-scale electrical energy storages. The column-andconstraint generation (C&CG) is adopted to solve the proposed integrated robust model, in which nonlinear natural gas network constraints are reformulated via a set of linear constraints. Numerical experiments signify the effectiveness of the proposed model for handling volatile electrical loads and renewable generations via the coordinated scheduling of electricity and natural gas systems.

Section: Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust coordination of interdependent electricity and natural gas systems in day-ahead scheduling for facilitating volatile renewable generations via power-to-gas technology

Liu

et al. 2017

“…As far as optimized operation is concerned, [17,18] proposed an optimal power flow model for IPGNs and then derived a solution by an interior point method and a multi-agent genetic algorithm, respectively. Uncertainties of intermittent energy resources and loads were taken into account in [19] to establish a probabilistic optimal power flow model for IPGNs based on a multilinear method.…”

Section: Introductionmentioning

confidence: 99%

Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded

Chen

Zhang

et al. 2017

As power to gas (P2G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically. With the intent of characterizing market behaviors of integrated electric power and natural gas networks (IPGNs) with P2G facilities, this paper establishes a steady-state model of P2G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow (SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network. The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2G facilities, will contribute more to renewable energy utilization and carbon emission reduction.Keywords Integrated electric power and natural gas networks (IPGNs), Market equilibrium, Power to gas (P2G), Slack energy flow (SEF)

“…In contrast to [1], [2] uses Latin hypercube sampling and the Gram-Schmidt sequence orthogonal method to improve sampling efficiency, and reduces computation time of the Monte Carlo simulation. In [3], probabilistic energy flow is analyzed in an integrated energy system by adopting the Monte Carlo simulation, which is innovative but time consuming. In terms of the probabilistic power flow method based on the cumulant, a probability distribution is obtained by the combination of the cumulant method and the Gram-Charlier expansion given in [4].…”

Section: Introductionmentioning

confidence: 99%

“…2) For the first time, a unified probabilistic power and gas flow calculation based on the cumulant method is proposed to analyze the effect of uncertain factors on the natural gas and electricity coupled system. This method is much faster than other existing methods of unified probabilistic power and gas flow, such as the Monte Carlo simulation used in [3]. 3) A new method of piecewise linearization is put forward to achieve a more precise fit to the probability distribution when random factors with large variation range appear in the coupled system.…”

Section: Introductionmentioning

confidence: 99%

Unified probabilistic gas and power flow

Lian

Bie

et al. 2017

The natural gas system and electricity system are coupled tightly by gas turbines in an integrated energy system. The uncertainties of one system will not only threaten its own safe operation but also be likely to have a significant impact on the other. Therefore, it is necessary to study the variation of state variables when random fluctuations emerge in the coupled system. In this paper, a multislack-bus model is proposed to calculate the power and gas flow in the coupled system. A unified probabilistic power and gas flow calculation, in which the cumulant method and Gram-Charlier expansion are applied, is first presented to obtain the distribution of state variables after considering the effects of uncertain factors. When the variation range of random factors is too large, a new method of piecewise linearization is put forward to achieve a better fitting precision of probability distribution. Compared to the Monte Carlo method, the proposed method can reduce computation time greatly while reaching a satisfactory accuracy.The validity of the proposed methods is verified in a coupled system that consists of a 15-node natural gas system and the IEEE case24 power system.