Comparison of methods for state prediction: Power Flow Decomposition (PFD), AC Power Transfer Distribution factors (AC-PTDFs), and Power Transfer Distribution factors (PTDFs)

Leveringhaus, Thomas; Hofmann, Lutz

doi:10.1109/appeec.2014.7066183

Cited by 20 publications

(7 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Energy storage constraints

0\le {P}_{m,t}^{\mathrm{dis}}\le {P}_{m,t}^{\mathrm{max}},

0\le {P}_{m,t}^{\mathrm{ch}}\le {P}_{m,t}^{\mathrm{max}},

\eta \sum \limits_{t=1}^T{P}_{m,t}^{\mathrm{ch}}-\frac{1}{\eta}\sum \limits_{t=1}^T{P}_{m,t}^{\mathrm{dis}}=0,

where

{P}_{m,t}^{\mathrm{max}}

is the upper limit of charging and discharging power. Power flow security constraints 36

{P}_l^{\mathrm{min}}\le {P}_{l,t}\le {P}_l^{\mathrm{max}},

P_{l}^{\min} \leq \sum_{h = 1}^{H} G_{l - h} P_{h, t} goodbreak+ \sum_{w = 1}^{W} G_{l - w} P_{w, t}^{rea},<...

…”

Section: Unit Commitment Optimization Model Considering Wind Turbine ...mentioning

confidence: 99%

Wasserstein‐metric‐based distributionally robust optimization method for unit commitment considering wind turbine uncertainty

Yan

Chen

et al. 2023

Engineering Reports

View full text Add to dashboard Cite

The penetration of wind turbines in the power grid is increasing rapidly. Still, the wind turbine output power has uncertainty, leading to poor grid reliability, affecting the grid's dispatching plan, and increasing the total cost. Thus, a distributionally robust optimization method for thermal power unit commitment considering the uncertainty of wind power is proposed. For this method, energy storage and interruptible load are added to simulate increasingly complex electricity consumption scenarios. Furthermore, the amount of load cutting reflects the satisfaction level of electricity consumption on the user side. Based on Wasserstein metric, an ambiguity set is established to reflect the probabilistic distribution information of the wind power uncertainty. An ambiguity set preprocessing method is proposed to depict the probability distribution of ambiguity set more clearly, to minimize the operation cost under the condition that the uncertainty of wind turbine output power obeys the extreme probabilistic distribution of the ambiguity set. The test case in a modified version of the IEEE 6‐bus system shows that the proposed method can flexibly adjust the robustness and economy of optimization decisions by controlling the sample size and the confidence of Wasserstein ambiguity set radius. In addition, the proposed ambiguity set preprocessing method can obtain more economical dispatching decisions with a smaller sample size.

show abstract

“…Energy storage constraints

0\le {P}_{m,t}^{\mathrm{dis}}\le {P}_{m,t}^{\mathrm{max}},

0\le {P}_{m,t}^{\mathrm{ch}}\le {P}_{m,t}^{\mathrm{max}},

\eta \sum \limits_{t=1}^T{P}_{m,t}^{\mathrm{ch}}-\frac{1}{\eta}\sum \limits_{t=1}^T{P}_{m,t}^{\mathrm{dis}}=0,

where

{P}_{m,t}^{\mathrm{max}}

is the upper limit of charging and discharging power. Power flow security constraints 36

{P}_l^{\mathrm{min}}\le {P}_{l,t}\le {P}_l^{\mathrm{max}},

P_{l}^{\min} \leq \sum_{h = 1}^{H} G_{l - h} P_{h, t} goodbreak+ \sum_{w = 1}^{W} G_{l - w} P_{w, t}^{rea},<...

…”

Section: Unit Commitment Optimization Model Considering Wind Turbine ...mentioning

confidence: 99%

Wasserstein‐metric‐based distributionally robust optimization method for unit commitment considering wind turbine uncertainty

Yan

Chen

et al. 2023

Engineering Reports

View full text Add to dashboard Cite

show abstract

“…A slack node must be defined with a known voltage magnitude and angle [20] as otherwise the Jacobian matrix is not invertible.…”

Section: Electricity-gas Power Flow a Electric Power Systemmentioning

confidence: 99%

Impact of Heat Pumps, Rooftop PV, and Hydrogen Blending on Gas-Electricity Distribution Networks in Northeast US

2023

View full text Add to dashboard Cite

The building sector is responsible for about 7 % of overall greenhouse gas emissions in the US. Cutting the emissions by electrifying heating and cooling supply through heat pumps (HPs) leads to an increase in electricity demand and potential overloading of lines and transformers in electricity distribution systems. Although many studies investigate the maximum potential for HPs in existing distribution systems in Europe, they neglect a potential relieving effect of combining HPs with rooftop photovoltaic (PV) systems as well as the consequence of coupling the electricity and gas system at distribution level. Hence, we investigate the effect of HPs and rooftop PV systems in a representative distribution system in Northeast US and the potential of coupling electricity and gas distribution systems. We show that generally no overloading in average US electric distribution systems occurs even under high realistic HP and PV adoption rates. Moreover, our results show that combining HPs and rooftop PV reduces the impact on the distribution system throughout the year with the greatest reduction in spring and fall. In contrast, the potential for injecting hydrogen on distribution level is technically very limited and not economic. Thus, electrolyzers at distribution level are not able to reduce congestion in the electricity system.

show abstract

“…As the nodal values are determined as relative to each other, an infinite number of solutions exists, leading to a Jacobian matrix which is mathematically singular [35]. To make the Jacobian matrix invertible a slack node is defined with a known voltage magnitude and angle and which also balances the EPS [35].…”

Section: A Electric Power Systemmentioning

confidence: 99%

A Joined Quasi-Steady-State Power Flow Calculation for Integrated Energy Systems

Dancker

Wolter

2022

IEEE Access

View full text Add to dashboard Cite

The network storage capability of district heating systems and gas systems can provide a considerable flexibility in integrated energy systems, increasing the use of volatile renewable energy generation. But the stronger the single energy systems are linked the more complex their operation becomes due to their increased interactions. To ensure a secure and reliable system operation while using the full potential of integrated energy systems, these interactions must be analyzed. Existing power flow calculation methods, however, assume a steady-state behavior of all energy systems in the integrated energy system, neglecting the network storage capability. Hence, this paper presents a joined quasi-steady-state power flow calculation method for integrated energy systems. Our method introduces the dynamic behavior of the district heating system arising from the temperature propagation and the dynamic behavior of the gas system due to the gas compressibility and propagation of hydrogen. In a comparison with a steady-state power flow calculation we show the considerable effect of the network storage on the operation of an integrated energy system. As our method enhances existing steady-state power flow calculation methods, it can be easily used for the same use cases but allowing the full potential of integrated energy systems to be investigated.INDEX TERMS Quasi-steady-state, integrated energy system, power flow calculation, Newton-Raphson method, gradient method.

show abstract

Comparison of methods for state prediction: Power Flow Decomposition (PFD), AC Power Transfer Distribution factors (AC-PTDFs), and Power Transfer Distribution factors (PTDFs)

Cited by 20 publications

References 11 publications

Wasserstein‐metric‐based distributionally robust optimization method for unit commitment considering wind turbine uncertainty

Wasserstein‐metric‐based distributionally robust optimization method for unit commitment considering wind turbine uncertainty

Impact of Heat Pumps, Rooftop PV, and Hydrogen Blending on Gas-Electricity Distribution Networks in Northeast US

A Joined Quasi-Steady-State Power Flow Calculation for Integrated Energy Systems

Contact Info

Product

Resources

About