Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

Hijazi, Hassan; Coffrin, Carleton; Hentenryck, Pascal Van

doi:10.1007/s12532-016-0112-z

Cited by 168 publications

(189 citation statements)

References 44 publications

Supporting

Mentioning

186

Contrasting

Order By: Relevance

“…In this model we make heavy use of bilinear relaxations introduced by McCormick in [17], [18] and widely applied in [8], [19], [20]. Intuitively, this relaxation formulates convex envelopes for bilinear terms.…”

Section: Relaxations For Bilinear Termsmentioning

confidence: 99%

“…This model is based on the seminal second order cone relaxations derived by [8]. For notional simplicity and brevity, we omit the terms and constraints related to line losses, currents, and shunt compensation.…”

Section: Ac-power Flow Modelmentioning

confidence: 99%

“…For notional simplicity and brevity, we omit the terms and constraints related to line losses, currents, and shunt compensation. The networks in our experimental results include some of these features and interested readers are invited to consult [8] for the details on how to incorporate these features.…”

Section: Ac-power Flow Modelmentioning

confidence: 99%

“…(21) and (22). In this paper we use the result of [8] to relax these equations to the following set of convex constraints:…”

Section: Ac-power Flow Modelmentioning

confidence: 99%

“…1 shows a schematic of the electricity and natural gas coupling infrastructure which is based on illustrations taken from [3], [4], [5], [6]. We focus on solving the computational challenges associated with this problem and we base our approach on recent advances in convex relaxations developed for power and gas systems [7], [8]. This paper does not address the issues associated with implementing the solutions of this model.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Sánchez

Bent

Backhaus

et al. 2016

2016 49th Hawaii International Conference on System Sciences (HICSS)

Self Cite

View full text Add to dashboard Cite

Section: Relaxations For Bilinear Termsmentioning

confidence: 99%

Section: Ac-power Flow Modelmentioning

confidence: 99%

Section: Ac-power Flow Modelmentioning

confidence: 99%

“…(21) and (22). In this paper we use the result of [8] to relax these equations to the following set of convex constraints:…”

Section: Ac-power Flow Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Sánchez

Bent

Backhaus

et al. 2016

2016 49th Hawaii International Conference on System Sciences (HICSS)

Self Cite

View full text Add to dashboard Cite

Performance comparison of optimum power flow based on the sequential second‐order cone programming in unbalanced low voltage distribution networks with distributed generators

Manamperi¹,

Ekanayake

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

A solution technique using sequential second-order cone programming to solve the optimum power flow problem in low voltage (LV) distribution networks with distributed generation is developed. A novel bound tightening method is suggested to get exact solutions with few iterations. A novel approximation method is suggested to increase exactness by approximating phase angle dependent components. The performance of the suggested solution method is compared with linear programming, genetic algorithm, particle swarm, sequential quadratic programming with multiple start points, and global search-based optimization methods. The exactness of the generated solutions is validated after comparison with a load flow. The proposed algorithm provides better performance in optimality, execution time, and exactness compared to other methods.distributed generation, optimum power flow, power distribution system, second-order cone programming | INTRODUCTIONOptimum power flow (OPF) is used as a tool to optimally control controllable devices such as smart inverters, batteries, tap changing transformers, and static var compensators in LV networks. OPF for transmission networks is widely discussed in the literature, and they are used in day-to-day operations in transmission system control centers. 1,2 With the increased penetration of renewable energy in low voltage distribution systems, the use of OPF for controlling power

show abstract

Evaluating demand response opportunities for power systems resilience using MILP and MINLP Formulations

et al. 2019

View full text Add to dashboard Cite

While peak shaving is commonly used to reduce power costs, chemical process facilities that can reduce power consumption on demand during emergencies (e.g., extreme weather events) bring additional value through improved resilience. For process facilities to effectively negotiate demand response (DR) contracts and make investment decisions regarding flexibility, they need to quantify their additional value to the grid. We present a grid‐centric mixed‐integer stochastic programming framework to determine the value of DR for improving grid resilience in place of capital investments that can be cost prohibitive for system operators. We formulate problems using both a linear approximation and a nonlinear alternating current power flow model. Our numerical results with both models demonstrate that DR can be used to reduce the capital investment necessary for resilience, increasing the value that chemical process facilities bring through DR. However, the linearized model often underestimates the amount of DR needed in our case studies. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. AIChE J, 65: e16508, 2019

show abstract

Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

Cited by 168 publications

References 44 publications

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Convex Optimization for Joint Expansion Planning of Natural Gas and Power Systems

Performance comparison of optimum power flow based on the sequential second‐order cone programming in unbalanced low voltage distribution networks with distributed generators

Evaluating demand response opportunities for power systems resilience using MILP and MINLP Formulations

Contact Info

Product

Resources

About