Robust Co-Optimization to Energy and Ancillary Service Joint Dispatch Considering Wind Power Uncertainties in Real-Time Electricity Markets

Ding, Tao; Wu, Zhongyu; Lv, Jiajun; Bie, Zhaohong; Zhang, Xianjun

doi:10.1109/tste.2016.2561967

Cited by 83 publications

(41 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For the uncertainty processing of wind power, most of the processing methods adopted in the previous research can be divided into two categories, namely robust optimization and stochastic optimization. References [6][7][8][9][10] adopt the idea of robust optimization to cope with the volatility of wind power. Reference [6] studies the wind power uncertainty of gas-electric integrated system coordination optimization and puts forward a two-stage distributionally robust optimization (DRO) model with the goal of minimum system total operating cost to analyze the impact of residents of gas load, abandon the wind punishment cost coefficient, and climb rate parameters on the final optimization results.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Reference [6] studies the wind power uncertainty of gas-electric integrated system coordination optimization and puts forward a two-stage distributionally robust optimization (DRO) model with the goal of minimum system total operating cost to analyze the impact of residents of gas load, abandon the wind punishment cost coefficient, and climb rate parameters on the final optimization results. Based on robust optimization, the literature [7] establishes an optimization model for joint scheduling of energy and auxiliary services markets that considered wind power uncertainty in the real-time power market and proposes redundant constraint reduction strategy to improve the computational efficiency of robust joint scheduling. Reference [8] utilizes distributionally robust chance constrained and interval optimization to handle the impact of wind power fluctuation.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

Dong¹,

Anyuan²,

Liu³

et al. 2019

Sustainability

View full text Add to dashboard Cite

Today, wind power is becoming an important energy source for the future development of electric energy due to its clean and environmentally friendly characteristics. However, due to the uncertainty of incoming wind, the utilization efficiency of wind energy is extremely low, which means the problem of wind curtailment becomes more and more serious. To solve the issue of wind power large-scale consumption, a two-stage stochastic optimization model is established in this paper. Different from other research frameworks, a novel two-side reserve capacity mechanism, which simultaneously takes into account supply side and demand side, is designed to ensure the stable consumption of wind power in the real-time market stage. Specifically, the reserve capacity of thermal power units is considered on the supply side, and the demand response is introduced as the reserve capacity on the demand side. At the same time, the compensation mechanism of reserve capacity is introduced to encourage generation companies (GENCOs) to actively participate in the power balance process of the real-time market. In terms of solution method, compared with the traditional k-means clustering method, this paper uses the K-means classification based on numerical weather prediction (K-means-NWP) scenario clustering method to better describe the fluctuation of wind power output. Finally, an example simulation is conducted to analyze the influence of reserve capacity compensation mechanism and system parameters on wind power consumption results. The results demonstrate that with the introduction of reserve capacity compensation mechanism, the wind curtailment quantity of the power system has a significant reduction. Besides, the income of GENCOs is gradually increasing, which motivates their enthusiasm to provide reserve capacity. Furthermore, the reserve capacity mechanism designed in this paper promotes the consumption of wind power and the sustainable development of renewable energy.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

Dong¹,

Anyuan²,

Liu³

et al. 2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…On account of the lack of fossil resources and environment protection demand, wind power is becoming one of the most rapidly growing renewable energy sources, and regarded as an appealing alternative to conventional power generated from fossil fuel, which plays a very important role in national energy policies all around the world. Because of its advantages of clean, low carbon and renewable energy, wind power has provided strong support for energy saving, emission reduction and environmental protection in various countries [1,2]. According to the data released in 2017, it has been stated that the global installed wind power capacity has been 539 GW by the end of 2017 and a new record will be set in the future.…”

Section: Introductionmentioning

confidence: 99%

Asymmetric GARCH type models for asymmetric volatility characteristics analysis and wind power forecasting

Chen

Zhang

Tao

et al. 2019

Prot Control Mod Power Syst

View full text Add to dashboard Cite

Wind power forecasting is of great significance to the safety, reliability and stability of power grid. In this study, the GARCH type models are employed to explore the asymmetric features of wind power time series and improved forecasting precision. Benchmark Symmetric Curve (BSC) and Asymmetric Curve Index (ACI) are proposed as new asymmetric volatility analytical tool, and several generalized applications are presented. In the case study, the utility of the GARCH-type models in depicting time-varying volatility of wind power time series is demonstrated with the asymmetry effect, verified by the asymmetric parameter estimation. With benefit of the enhanced News Impact Curve (NIC) analysis, the responses in volatility to the magnitude and the sign of shocks are emphasized. The results are all confirmed to be consistent despite varied model specifications. The case study verifies that the models considering the asymmetric effect of volatility benefit the wind power forecasting performance.

show abstract

“…One is to determine the base point of the generation output while satisfying the power balance for all possible wind power outputs, followed by the computation of participation factors, which is an effective solution for the penetration of wind power into the power system [4]. In addition, a robust co-optimization to energy and ancillary service joint dispatch considering wind power uncertainties in real-time electricity markets was proposed in [5]. Both models in [4,5] are based on Direct Current (DC) power flow.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, a robust co-optimization to energy and ancillary service joint dispatch considering wind power uncertainties in real-time electricity markets was proposed in [5]. Both models in [4,5] are based on Direct Current (DC) power flow. Therefore, the participation factors employed in those papers to produce adjustable generation outputs immune to uncertain wind power generation and the robust optimization model can be equivalently transformed into a linear programming model.…”

Section: Introductionmentioning

confidence: 99%

Robust Co-Optimization to Energy and Reserve Joint Dispatch Considering Wind Power Generation and Zonal Reserve Constraints in Real-Time Electricity Markets

Yun

Ding

et al. 2017

Applied Sciences

Self Cite

View full text Add to dashboard Cite

This paper proposes an energy and reserve joint dispatch model based on a robust optimization approach in real-time electricity markets, considering wind power generation uncertainties as well as zonal reserve constraints under both normal and N-1 contingency conditions. In the proposed model, the operating reserves are classified as regulating reserve and spinning reserve according to the response performance. More specifically, the regulating reserve is usually utilized to reduce the gap due to forecasting errors, while the spinning reserve is commonly adopted to enhance the ability for N-1 contingencies. Since the transmission bottlenecks may inhibit the deliverability of reserve, the zonal placement of spinning reserve is considered in this paper to improve the reserve deliverability under the contingencies. Numerical results on the IEEE 118-bus test system show the effectiveness of the proposed model.

show abstract

Robust Co-Optimization to Energy and Ancillary Service Joint Dispatch Considering Wind Power Uncertainties in Real-Time Electricity Markets

Cited by 83 publications

References 26 publications

Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

Asymmetric GARCH type models for asymmetric volatility characteristics analysis and wind power forecasting

Robust Co-Optimization to Energy and Reserve Joint Dispatch Considering Wind Power Generation and Zonal Reserve Constraints in Real-Time Electricity Markets

Contact Info

Product

Resources

About