Convex Relaxations and Approximations of Chance-Constrained AC-OPF Problems

Halilbašić, Lejla; Chatzivasileiadis, Spyros

doi:10.1109/tpwrs.2018.2874072

Cited by 33 publications

(26 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…McCormick relaxation [23], to investigate the possibility of adding sufficient conditions to tighten the SOC relaxation [18], and to explore alternatives for ex-post feasibility recovery [24].…”

Section: Discussionmentioning

confidence: 99%

Coordination of Power and Natural Gas Systems: Convexification Approaches for Linepack Modeling

Schwele

Ordoudis

Kazempour

et al. 2019

2019 IEEE Milan PowerTech

Self Cite

View full text Add to dashboard Cite

Utilizing operational flexibility from natural gas networks can foster the integration of uncertain and variable renewable power production. We model a combined power and natural gas dispatch to reveal the maximum potential of linepack, i.e., energy storage in the pipelines, as a source of flexibility for the power system. The natural gas flow dynamics are approximated by a combination of steady-state equations and varying incoming and outgoing flows in the pipelines to account for both natural gas transport and linepack. This steadystate natural gas flow results in a nonlinear and nonconvex formulation. To cope with the computational challenges, we explore convex quadratic relaxations and linear approximations. We propose a novel mixed-integer second-order cone formulation including McCormick relaxations to model the bidirectional natural gas flow accounting for linepack. Flexibility is quantified in terms of system cost compared to a dispatch model that either neglects linepack or assumes infinite storage capability. Index Terms-Combined power and natural gas dispatch, convexification, McCormick relaxation, second-order cone program, steady-state gas flow.

show abstract

Section: Discussionmentioning

confidence: 99%

Coordination of Power and Natural Gas Systems: Convexification Approaches for Linepack Modeling

Schwele

Ordoudis

Kazempour

et al. 2019

2019 IEEE Milan PowerTech

Self Cite

View full text Add to dashboard Cite

show abstract

“…Alternatively, one can use linearized AC power flow approximations, e.g. [39], [40], or convex (second-order) relaxations, [41], that improve the model accuracy at a modest increase in computing times. Notably, models for distribution power flows can take advantage of typically radial distribution network structures, which allow for linear LindDistFlow and second-order DistFlow formulations, [42], that are capable of providing more accurate tractable solutions then DC approximation.…”

Section: ) Electricity Supplymentioning

confidence: 99%

A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications

et al. 2020

View full text Add to dashboard Cite

Due to proliferation of energy efficiency measures and availability of the renewable energy resources, traditional energy infrastructure systems (electricity, heat, gas) can no longer be operated in a centralized manner under the assumption that consumer behavior is inflexible, i.e. cannot be adjusted in return for an adequate incentive. To allow for a less centralized operating paradigm, consumer-end perspective and abilities should be integrated in current dispatch practices and accounted for in switching between different energy sources not only at the system but also at the individual consumer level. Since consumers are confined within different built environments, this paper looks into an opportunity to control energy consumption of an aggregation of many residential, commercial and industrial consumers, into an ensemble. This ensemble control becomes a modern demand response contributor to the set of modeling tools for multi-energy infrastructure systems. arXiv:2005.02339v1 [eess.SY] 5 May 2020

show abstract

“…Since wind power and photovoltaic output are described in probabilistic sequences, the opportunity constraint theory [23]- [25] is used to deal with the wind power and photovoltaic output related constraints, then the equation 3, (4), (7) can be converted into the following forms.…”

Section: Determination Processing Of Uncertainty Constraintsmentioning

confidence: 99%

Medium and Long-Term Electricity Trading Considering Renewable Energy Participation

Fan

Zhang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

The medium and long-term electricity trading approach considering uncertain renewable energy participation is established based on the bi-level model in this paper. The upper-level is designed to maximize the profitability of power generation companies, while the lower-level aims to maximize the social welfare. Afterwards, a hybrid algorithm combining the discrete and continuous particle swarm optimization is proposed to solve the upper-level model, and the nonlinear programming method is used to address the lower-level model. Finally, verification is performed on the improved IEEE 39-bus system, and simulation results demonstrate that the proposed approach could indeed improve the profit of renewable energy as well as increase the social welfare of power generation enterprises. INDEX TERMS Renewable energy, electricity market, medium and long-term electricity trading, particle swarm optimization.

show abstract

Convex Relaxations and Approximations of Chance-Constrained AC-OPF Problems

Cited by 33 publications

References 29 publications

Coordination of Power and Natural Gas Systems: Convexification Approaches for Linepack Modeling

Coordination of Power and Natural Gas Systems: Convexification Approaches for Linepack Modeling

A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications

Medium and Long-Term Electricity Trading Considering Renewable Energy Participation

Contact Info

Product

Resources

About