Application of Cost-CVaR model in determining optimal spinning reserve for wind power penetrated system

Wu, Junli; Zhang, Buhan; Deng, Weisi; Zhang, Kaimin

doi:10.1016/j.ijepes.2014.10.051

Cited by 25 publications

(11 citation statements)

References 17 publications

(29 reference statements)

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“…With this end in view, wind power uncertainty modelling and further establishing the effective control strategy have attracted much attention recently. In this regard, many researchers have modelled the uncertain wind power generation impacts using different methodologies [2][3][4][5]. Robust optimisation has been proposed to model the uncertain nature of wind power in a joint energy and ancillary service market [2].…”

Section: Introductionmentioning

confidence: 99%

“…The stochastic dominance concept is proposed to model risk in a power system with dispersed generation [3]. The cost‐CVaR model is the other studied approach to evaluate the associated risk of the uncertain wind power forecast [4]. The mentioned model is utilised to determine the optimal spinning reserve in a wind integrated power system.…”

Section: Introductionmentioning

confidence: 99%

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Social welfare maximisation of market based wind integrated power systems by simultaneous coordination of transmission switching and demand response programs

Arasteh

Riahy

2019

IET Renewable Power Generation

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The non-preventable ever-increasing rate of wind power generation in market-based power systems faces the operators with challenging situations for making optimal decisions. So, it is essential to equip the operators with applicable control strategies and further corresponding control facilities. Moreover, the high-priority of cheap wind power utilisation increases the probability of transmission lines congestion. Therefore, different solutions such as transmission switching (TS) and demand response (DR) programs have been recently introduced to manage the intermittent wind power generations. Accordingly, this study addresses the social welfare maximisation problem with coordinated control of TS and DR facilities to handle the regarding uncertainties using yet another linear matrix inequality parser (YALMIP). In fact, rapid algorithm and powerful employed solvers as well as simplicity of use, make YALMIP a practical modelling and optimisation toolbox. In this respect, the MOSEK solver is preferred by YALMIP to solve the proposed mixed integer linear programming problem. In addition, wind power uncertainty is modelled using the discrete-time Markov chain approach and optimisations are performed on the 8-bus and the large-scale IEEE 118-bus test systems. Results show that the proposed control strategy is highly capable of maximising social welfare by determining the optimal control commands in a real-time manner. P transition probability matrix

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Social welfare maximisation of market based wind integrated power systems by simultaneous coordination of transmission switching and demand response programs

Arasteh

Riahy

2019

IET Renewable Power Generation

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“…Ref. [26] proposed a Cost-CVAR model to determine an optimal spinning reserve for a wind power penetration system. Although some works have considered the uncertainties of renewable energy, the uncertainties of WTs and PVs have seldom been considered simultaneously.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

Lin

Yang

et al. 2018

Energies

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This paper presents the scheduling dispatch of a microgrid (MG), while considering renewable energy, battery storage systems, and time-of-use price. For the risk evaluation of an MG, the Value-at-Risk (VAR) is calculated by using the Historical Simulation Method (HSM). By considering the various confidence levels of the VAR, a scheduling dispatch model of the MG is formulated to achieve a reasonable trade-off between the risk and cost. An Improved Bee Swarm Optimization (IBSO) is proposed to solve the scheduling dispatch model of the MG. In the IBSO procedure, the Sin-wave Weight Factor (SWF) and Forward-Backward Control Factor (FBCF) are embedded in the bee swarm of the BSO to improve the movement behaviors of each bee, specifically, its search efficiency and accuracy. The effectiveness of the IBSO is demonstrated via a real MG case and the results are compared with other methods. In either a grid-connected scenario or a stand-alone scenario, an optimal scheduling dispatch of MGs is carried out, herein, at various confidence levels of risk. The simulation results provide more information for handling uncertain environments when analyzing the VAR of MGs.

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“…Both [19,20] also consider wind power generation as an operating risk and propose an algorithm based on non-parametric kernel density estimation and a model for a short-term future forecasting using a conditional probability approach to reduce the risk. In [21,22], wind power uncertainty is modeled as Gaussian distribution and finite-state Markove chain, respectively. Then reserve capacity which could minimize the expected cost is calculated based on each model.…”

Section: Introductionmentioning

confidence: 99%

Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand

et al. 2016

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Abstract:The use of appropriate hourly reserve margins can maintain power system security by balancing supply and demand in the presence of errors in the forecast demand, generation outages, or errors in the forecast of wind power generation. Because the cost of unit commitment increases with larger reserve margins, cost analysis to determine the most economical reserve margin is an important issue in power system operation. Here, we define the "short-term reliability of balance" and describe a method to determine the reserve margin based on the short-term reliability of balance. We describe a case study, in which we calculate the reserve margin using this method with various standards of short-term reliability of balance. A cost analysis is then performed to determine the most economic standard, and a comparison between our method and a conventional method is carried out. The results show that our method with an economic short-term reliability of balance enables more reliable and efficient operation of the power system. Moreover, with an hourly reserve margin, we show that an increase in wind power generation can result in a significant decrease in the operating cost, which makes wind power generation economically viable.

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Application of Cost-CVaR model in determining optimal spinning reserve for wind power penetrated system

Cited by 25 publications

References 17 publications

Social welfare maximisation of market based wind integrated power systems by simultaneous coordination of transmission switching and demand response programs

Social welfare maximisation of market based wind integrated power systems by simultaneous coordination of transmission switching and demand response programs

An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand

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