Stochastic optimal power flow based on conditional value at risk and distributional robustness

Summers, Tyler H.; Warrington, Joseph; Morari, Manfred; Lygeros, John

doi:10.1016/j.ijepes.2015.02.024

Cited by 115 publications

(101 citation statements)

References 32 publications

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“…Additionally, a Petri net (PN) based computational synchronization mechanism is proposed to solve OPF smart grid transmission system (OPFSG) problem. In 2015, Summers et al [60] presented a stochasticmultiperiod OPF problem, for which a family of convex rough calculations is used to trade-off cost against security in different ways. In 2016, Tazvinga et al [113] presented an optimal model of a photovoltaic-diesel-battery (PDB) based hybrid energy management system to reduce both fuel costs and battery wear costs.…”

Section: Distributed Generation (Dg) In 2011 Amanifar Andmentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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The exhaustive knowledge of optimal power flow (OPF) methods is critical for proper system operation and planning, since OPF methods are utilized for finding the optimal state of any system under system constraint conditions, such as loss minimization, reactive power limits, thermal limits of transmission lines, and reactive power optimization. Incorporating renewable energy sources optimized the power flow of system under different constraints. This work presents a comprehensive study of optimal power flows methods with conventional and renewable energy constraints. Additionally, this work presents a progress of optimal power flow solution from its beginning to its present form. Authors classify the optimal power flow methods under different constraints condition of conventional and renewable energy sources. The current and future applications of optimal power flow programs in smart system planning, operations, sensitivity calculation, and control are presented. This study will help the engineers and researchers to optimize power flow with conventional and renewable energy sources.

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Section: Distributed Generation (Dg) In 2011 Amanifar Andmentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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“…In Section II-A, we model uncertainty in stochastic production, while in Section II-B we describe the bidding process in a market designed to accommodate probabilistic offers. Finally, in Section II-C we formally define the risk measure in consistence with literature [8].…”

Section: Marketsmentioning

confidence: 99%

“…Authors in [8] propose a stochastic optimal power flow (OPF) model that gives optimal policies regarding scheduling of controllable devices within a power network based on chance constraints. Solutions depend on how the probabilistic constraints are formulated with the model relying on access to the variance of forecast errors.…”

Section: Introductionmentioning

confidence: 99%

“…The model is based on DC power flow, while unit commitment (UC) is not considered as part of the problem. Both approaches in [8], [9] contribute on the overall discussion, however they face some limitations: i) risk is only associated to a part of operational uncertainty and ii) they are based on conventional market clearing mechanisms using only deterministic offers.…”

Section: Introductionmentioning

confidence: 99%

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A robust optimisation approach using CVaR for unit commitment in a market with probabilistic offers

Bukhsh

Papakonstantinou

2016

2016 IEEE International Energy Conference (ENERGYCON)

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Abstract-The large scale integration of renewable energy sources (RES) challenges power system planners and operators alike as it can potentially introduce the need for costly investments in infrastructure. Furthermore, traditional market clearing mechanisms are no longer optimal due to the stochastic nature of RES. This paper presents a risk-aware market clearing strategy for a network with significant shares of RES. We propose an electricity market that embeds the uncertainty brought by wind power and other stochastic renewable sources by accepting probabilistic offers and use a risk measure defined by conditional value-at-risk (CVaR) to evaluate the risk of high re-dispatching cost due to the mis-estimation of renewable energy. The proposed model is simulated on a 39-bus network, whereby it is shown that significant reductions can be achieved by properly managing the risks of mis-estimation of stochastic generation.

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“…Mathematical methodologies introduced above provide some motivation for solving ED problems with ambiguous distribution information of random variables in power system analysis, see recent references . Papers proposed DRO‐based unit commitment (UC) via 2‐stage optimization.…”

Section: Introductionmentioning

confidence: 99%

A distributionally robust optimization-based risk-limiting dispatch in power system under moment uncertainty

Tong¹,

Luo

Yang

et al. 2017

Int. Trans. Electr. Energ. Syst.

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Summary In this paper, we study the risk‐limiting dispatch (RLD) of power system in the case that the distribution information of random variable is ambiguous. Under an ellipsoidal moment uncertainty of the mean and the covariance matrix, we develop the distributionally robust optimization approach to set up a new RLD model, named robust RLD (RRLD for short). The RRLD considers simultaneously the risk of unsafe operation limit by conditional Value‐at‐Risk management. We further convert the RRLD model into a solvable convex optimization for a special case that the operation constraint is addressed on the overloading transmission current. The new RRLD model is a development and generalization of the traditionary economic dispatch and the RLD approach. Meanwhile, our research extends the distributionally robust optimization application in portfolio problems to a security economic operation of power system. The IEEE‐14 and IEEE‐30 bus system are chosen as numerical test systems. Preliminary numerical examples show the validity of the model and its reformulation.

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Stochastic optimal power flow based on conditional value at risk and distributional robustness

Cited by 115 publications

References 32 publications

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

A robust optimisation approach using CVaR for unit commitment in a market with probabilistic offers

A distributionally robust optimization-based risk-limiting dispatch in power system under moment uncertainty

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