Quantifying Spinning Reserve in Systems with Significant Wind Power Penetration

Chang, Xuefei; Lv, Xiangyu; Liu, Zuoming

doi:10.1109/appeec.2012.6307089

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…With the significant inclusion of wind power in the portfolio of a county or region, it is no longer adequate to deal with the UC problem in the traditional way [3]. The uncertainty in wind generation is at least one order of magnitude higher than the uncertainty in load [4].…”

Section: Introductionmentioning

confidence: 98%

Risk and unit commitment decisions in scenarios of wind power uncertainty

2016

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a b s t r a c tThis paper addresses the problem of decision making in Unit Commitment in systems with a significant penetration of wind power. Traditional approaches to Unit Commitment are inadequate to fully deal with the uncertainties associated to wind, represented by scenarios of forecasted wind power qualified by probabilities. Departing from a critique of planning paradigms, the paper argues that a stochastic programming approach, while a step in the good direction, is insufficient to model all aspects of the decision process and therefore proposes the adoption of models based on a Risk Analysis paradigm. A case study is worked out reinforcing this perspective. In a multi-objective context, the properties of the cost vs. risk Pareto-optimal fronts are analyzed, where risk may be represented by aversion to a worst scenario or a worst event. It is shown that the Pareto-optimal front may not be convex, which precludes a simplistic use of tradeoff concepts. It is also shown that decisions based on stochastic programming may in fact put the system at risk. An evaluation of risk levels and cost of hedging against undesired events is proposed as the paradigm to be followed in Unit Commitment decision making.

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Section: Introductionmentioning

confidence: 98%

Risk and unit commitment decisions in scenarios of wind power uncertainty

2016

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“…To mitigate these challenges, transmission system operators (TSO) encourage all energy sectors to provide PFC services through ancillary service markets. In these circumstances, different sources can be used to regulate frequency, such as conventional generation units [2], demand-side management…”

Section: Introductionmentioning

confidence: 99%

Optimum Operation of Battery Storage System in Frequency Containment Reserves Markets

Divshali

Evens

2020

IEEE Trans. Smart Grid

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This paper focuses on the bidding strategy and online control methodology of battery storage systems (BSS) to participate in the frequency containment reserve (FCR) market. The new technical requirements for the FCR markets in the Nordic power system does not allow controlling the BSS in other ways than on the basis of frequency. Therefore, control mechanisms such as recovering the state of charge (SOC) whenever the power system frequency is in its acceptable (deadband) range cannot be used. In this regard, this paper proposes and compares different control mechanisms to recover the SOC that are in line with the new regulation and maximizes the BSS profit using the lifetime model of the BSS. In order to compare different control mechanisms, this paper investigates the behaviour of a large BSS unit installed in the Helsinki area by simulating the proposed strategies over measured frequency and market data from 2014 till 2019.

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