Optimal joint demand and virtual bidding for a strategic retailer in the short-term electricity market

Xiao, Dongliang; Prado, Josue Campos do; Wang, Qiao

doi:10.1016/j.epsr.2020.106855

Cited by 51 publications

(25 citation statements)

References 28 publications

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“…Equation (15) limits the voltage at the low-voltage level of the substation. The security constraint of the distribution network is represented by (16) and (17).…”

Section: ) Bus Voltage Constraintsmentioning

confidence: 99%

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Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Yuan

Zhu

et al. 2021

Journal of Modern Power Systems and Clean Energy

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Successful distributed photovoltaic (PV) planning now requires a hosting capacity assessment process that accounts for an appropriate model of PV output and its uncertainty. This paper explores how the PV hosting capacity of distribution networks can be increased by means of spatial correlation among distributed PV outputs. To achieve this, a novel PV hosting capacity assessment method is proposed to account for arbitrary geographically dispersed distributed PVs. In this method, the empirical relation between the spatial correlation coefficient and distance is fitted by historical data in one place and then applied to model the joint probability distribution of PV outputs at a neighboring location. To derive the PV hosting capacity at candidate locations, a stochastic PV hosting capacity assessment model that aims to maximize the PV hosting capacity under thermal and voltage constraints is proposed. Benders decomposition algorithm is also employed to reduce the computational cost associated with the numerous sampling scenarios. Finally, a rural 59-bus distribution network in Suzhou, China, is used to demonstrate the effectiveness of the proposed PV hosting capacity assessment methodology and the significant benefits obtained by increasing geographical distance.

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“…Equation (15) limits the voltage at the low-voltage level of the substation. The security constraint of the distribution network is represented by (16) and (17).…”

Section: ) Bus Voltage Constraintsmentioning

confidence: 99%

“…Since inflexible operation rules usually lead to an uneconomic decision in planning, some works try to balance the DG curtailment risk and investment cost. For instance, [17] and [18] employ the conditional value at risk (CVaR) and stochastic dominance technique to gain a more efficient planning result.…”

Section: Introductionmentioning

confidence: 99%

Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Yuan

Zhu

et al. 2021

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

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“…Meta-heuristic algorithms have been shown to overcome several real-world problems in a reasonable time with high accuracy [17][18][19][20][21][22] and therefore have been widely applied for tackling the parameter identification problem (PIP) of PV models. This section reviews the major applications and their shortfalls.…”

Section: Introductionmentioning

confidence: 99%

Recent Meta-Heuristic Algorithms with a Novel Premature Covergence Method for Determining the Parameters of PV Cells and Modules

et al. 2021

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Currently, the incorporation of solar panels in many applications is a booming trend, which necessitates accurate simulations and analysis of their performance under different operating conditions for further decision making. In this paper, various optimization algorithms are addressed comprehensively through a comparative study and further discussions for extracting the unknown parameters. Efficient use of the iterations within the optimization process may help meta-heuristic algorithms in accelerating convergence plus attaining better accuracy for the final outcome. In this paper, a method, namely, the premature convergence method (PCM), is proposed to boost the convergence of meta-heuristic algorithms with significant improvement in their accuracies. PCM is based on updating the current position around the best-so-far solution with two-step sizes: the first is based on the distance between two individuals selected randomly from the population to encourage the exploration capability, and the second is based on the distance between the current position and the best-so-far solution to promote exploitation. In addition, PCM uses a weight variable, known also as a controlling factor, as a trade-off between the two-step sizes. The proposed method is integrated with three well-known meta-heuristic algorithms to observe its efficacy for estimating efficiently and effectively the unknown parameters of the single diode model (SDM). In addition, an RTC France Si solar cell, and three PV modules, namely, Photowatt-PWP201, Ultra 85-P, and STM6-40/36, are investigated with the improved algorithms and selected standard approaches to compare their performances in estimating the unknown parameters for those different types of PV cells and modules. The experimental results point out the efficacy of the PCM in accelerating the convergence speed with improved final outcomes.

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“…The aforementioned implies that DR penetration can be higher than the expected penetration levels [8], [9]. Uses of DR programs in the distribution operation with a significant amount of Distributed Generation (DG) based on renewable energy are usually combined to reduce the DER forecast uncertainty [10]. Some DR strategies were based on other technologies like DG to complement some schemes and avoid the total disconnection of it [11].…”

Section: Introductionmentioning

confidence: 99%

“…Authors in [4], defines that it was necessary to include data analyses to adjust the different behavior and implement a Multi Energy Systems that combine the distributed energy resources. With the DR's integration, the SO can manage the distributed energy resources, and the customer can offer their services to maintain the balance between demand and generation [10]. Different types of loads allow the time of response, which is necessary to categorize and reduce the impact of the distributed generation's fluctuation [28]- [30].…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Load Modeling to Analyze the Frequency of System Including Demand Response: A Colombian Study Case

et al. 2021

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This paper analyzes the potential impact of implementing demand response strategies in a power system. This work aims to present a methodology to evaluate three demand response models to reduce frequency variations in the system. The method starts with the modeling of the system load and the demand response strategies. The power loads are modeled through active power and reactive power measurements in the system's different buses. A data-driven methodology is proposed to obtain three profiles that simulate residential, commercial, and industrial users' behavior. Mathematical modeling is proposed for demand response strategies. Time of Use tariff, Solar PV Distributed Generation, and Load Curtailment are the strategies used for residential, commercial, and industrial users, respectively. A brand-new combination of scenarios is developed in this paper with different penetration levels of the demand response strategy. Besides, a novel analysis of the frequency profile is performed for the proposed scenarios. A modified IEEE-39 power system is proposed, adjusting generation and demand using the Colombian demand profile and the generating units' energy mix. The results indicate that the implementation of demand response strategies improves the system's frequency profile. The frequency drop was reduced by 11.4 %, and power generator units released up to 2.1 GWh through the day with the implementation of the DR strategies.

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Optimal joint demand and virtual bidding for a strategic retailer in the short-term electricity market

Cited by 51 publications

References 28 publications

Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Recent Meta-Heuristic Algorithms with a Novel Premature Covergence Method for Determining the Parameters of PV Cells and Modules

Data-Driven Load Modeling to Analyze the Frequency of System Including Demand Response: A Colombian Study Case

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