On critical timescale of real-time power balancing in power systems with intermittent power sources

Wang, Zongjie; Guo, Zhishan

doi:10.1016/j.epsr.2017.10.022

Cited by 19 publications

(13 citation statements)

References 22 publications

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“…when +∞ is selected for time t, E (+∞) = A. According to (18), the relationship between the amplitude A i of each time period uncertainty function E 1 , E 2 , • • • E n and the amplitude A of the total uncertainty function E is defined as follows:…”

Section: A Time Aggregation Of the Uncertainty Functionmentioning

confidence: 99%

“…Therefore, the DCS of PSHPRPSs should add a short time scale power balance link to maintain the power balance of power grids. To address significant day-ahead prediction errors in PSHPRPSs, [18] proposed a three timescale DCS that is coordinated by day-ahead dispatching, realtime dispatching, and AGC. Similarly, [19] proposed a four timescale DCS that is coordinated by day-ahead dispatching, rolling planning, real-time dispatching, and AGC.…”

Section: Introductionmentioning

confidence: 99%

“…Previous researchers examining the design of DCSs [28]- [31] set the CTS of real-time dispatching to 0.25 h, 1 h, or 4 h. However, these researchers usually choose the CTS of real-time dispatching based on experience rather than theoretical research. Wang et al [32] designed the uncertainty function to select the CTS of real-time dispatching by describing the functional relationship between the power prediction error of URESs and the prediction lead time. However, CTSs that are selected by this method change with the different daily prediction error.…”

Section: Introductionmentioning

confidence: 99%

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Selection of a Critical Time Scale of Real-Time Dispatching for Power Systems With High Proportion Renewable Power Sources

Chen

Guo

et al. 2020

IEEE Access

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The power prediction error of uncertain renewable energy sources (URESs) affects the power balance of a power grid. In the power systems with high proportion renewable power sources (PSHPRPSs), automatic generation control (AGC) cannot accommodate the day-ahead power prediction error. The dispatching control system (DCS) of PSHPRPSs adds real-time dispatching links to modify the day-ahead dispatching plan so that the grid power error is within the range of AGC accommodation. This paper proposes a critical time scale (CTS) selection algorithm based on time aggregation characteristics for real-time dispatching of PSHPRPSs and calculates the annual CTS of real-time dispatching of power grids. The uncertainty function is used to describe the relationship between the prediction error of the URESs and the prediction lead time. The total uncertainty function is calculated based on the time aggregation characteristics and is used to select the annual CTS of real-time dispatching. The proposed algorithm quantitatively describes the relationship between the CTS and the operation proportion of URESs and also AGC accommodation capacity. The calculated annual CTS not only ensures the power balance of the power grid, but also avoids the daily change of the CTS. Using the data of URESs in the Irish power grid, the feasibility of the proposed method was verified. The research results of this paper are helpful to accommodate the day-ahead power prediction error of URESs and maintain the safe operation of power grid. INDEX TERMS Uncertain renewable energy sources, power prediction error, real-time dispatching, critical time scale, time aggregation characteristics.

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Section: A Time Aggregation Of the Uncertainty Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Selection of a Critical Time Scale of Real-Time Dispatching for Power Systems With High Proportion Renewable Power Sources

Chen

Guo

et al. 2020

IEEE Access

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“…First, to enhance different forecasting methods reduces the forecasting error [4]. Second is accommodation, which means to allocate the accommodation reserves from controllable power sources to deal with uncertainties [5]. Third is adjustment, which means to adjust the current dispatch control systems from power balancing perspective [6].…”

Section: Introductionmentioning

confidence: 99%

“…Day-ahead scheduling adjusts the controllable power sources to balance day-ahead forecast value and arrange accommodation and AGC reserves [8]. Real-time dispatch corrects the "vague" day-ahead forecasting with the "clear" real time forecasting value, and balances the real time forecasting value with the accommodation reserve [9]. AGC corrects the "clear" real time forecasting value with the accurate actual value, and balances the actual value with the AGC reserve [10].…”

Section: Introductionmentioning

confidence: 99%

Optimal Dispatch in Power Systems with Intermittent Power Sources

Peng¹

2020

CWEEE

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With the increasing integration of intermittent power sources (IPSs) into the power system, the uncertainty of IPSs requires solution and current dispatch system needs improvement. This paper aims to generate the optimal dispatch plan for day-ahead scheduling and real-time dispatch using the proposed model of characteristic optimal power flow (COPF). The integral time period represented by the median load point and the heavy and light load point with simplicity and accuracy. Simulation case studies on a 30-bus system are presented, which shows that COPF is an effective model to generate the optimal dispatch plan for power systems with high penetration of IPSs.

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Quantitative characterization of uncertainty levels of intermittent power sources

Wang

Guo

2018

Journal of Renewable and Sustainable Energy

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This paper designs a statistical quantification towards the intermittent power uncertainty in power systems. A negative-exponential forecast uncertainty function is constructed to represent the relationship between the statistics of forecast error of a single intermittent power source and time advance. Subsequently, other kinds of statistical functions are proposed to characterize the statistical uncertainty of multiple intermittent power sources and all power sources, namely the sum statistical functions, the equivalent statistical functions, and the contour statistical functions. Based on a large amount of historical observations, these functions are employed to statistically quantify the forecast uncertainty of a single intermittent power source, multiple intermittent power sources as well as all power sources. Historical data sampled from real wind farms and solar sites demonstrates the effectiveness of the proposed method.

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On critical timescale of real-time power balancing in power systems with intermittent power sources

Cited by 19 publications

References 22 publications

Selection of a Critical Time Scale of Real-Time Dispatching for Power Systems With High Proportion Renewable Power Sources

Selection of a Critical Time Scale of Real-Time Dispatching for Power Systems With High Proportion Renewable Power Sources

Optimal Dispatch in Power Systems with Intermittent Power Sources

Quantitative characterization of uncertainty levels of intermittent power sources

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