Abstract 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 multi-slack-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 v...
This paper proposes a data-driven chance-constrained optimal gas-power flow (OGPF) calculation metho...
Load flow is highly uncertain with the large-scale integration of wind power. It is unrealistic to a...
In this paper, the authors apply a surrogate model-based method for probabilistic power flow (PPF) i...
Abstract The increasing adoption of gas-fired power plants directly strengthens the coupling between...
The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are l...
With the deep coupling of electricity, heat, and gas systems, the uncertainties in renewable energy ...
This paper proposes a probabilistic power flow (PPF) method considering continuous and discrete vari...
In this paper a framework based on the decomposition of the first-order optimality conditions is des...
With the large-scale wind power penetration, probabilistic power flow plays an important role in pow...
A method for solving a probabilistic power flow that deals with the uncertainties of (i) wind genera...
The traditional cumulant method (CM) for probabilistic optimal power flow (P-OPF) needs to perform l...
The increase of wind generation (WG) has challenged the conventional way of probabilistic load flow ...
In a power system with high penetration of variable Renewable Energy Sources (vRES), the high uncert...
This paper shows a practice to raise the reliability of an electric power system by the installation...
The deepening penetration of renewable resources, such as wind and photovoltaic solar, has introduc...
This paper proposes a data-driven chance-constrained optimal gas-power flow (OGPF) calculation metho...
Load flow is highly uncertain with the large-scale integration of wind power. It is unrealistic to a...
In this paper, the authors apply a surrogate model-based method for probabilistic power flow (PPF) i...
Abstract The increasing adoption of gas-fired power plants directly strengthens the coupling between...
The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are l...
With the deep coupling of electricity, heat, and gas systems, the uncertainties in renewable energy ...
This paper proposes a probabilistic power flow (PPF) method considering continuous and discrete vari...
In this paper a framework based on the decomposition of the first-order optimality conditions is des...
With the large-scale wind power penetration, probabilistic power flow plays an important role in pow...
A method for solving a probabilistic power flow that deals with the uncertainties of (i) wind genera...
The traditional cumulant method (CM) for probabilistic optimal power flow (P-OPF) needs to perform l...
The increase of wind generation (WG) has challenged the conventional way of probabilistic load flow ...
In a power system with high penetration of variable Renewable Energy Sources (vRES), the high uncert...
This paper shows a practice to raise the reliability of an electric power system by the installation...
The deepening penetration of renewable resources, such as wind and photovoltaic solar, has introduc...
This paper proposes a data-driven chance-constrained optimal gas-power flow (OGPF) calculation metho...
Load flow is highly uncertain with the large-scale integration of wind power. It is unrealistic to a...
In this paper, the authors apply a surrogate model-based method for probabilistic power flow (PPF) i...