Grid-Specific Co-Optimization of Incentive for Generation Planning in Power Systems With Renewable Energy Sources

Parizy, Ehsan Saeidpour; Choi, Seungdeog; Bahrami, Hamid Reza

doi:10.1109/tste.2019.2914875

Cited by 31 publications

(9 citation statements)

References 25 publications

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“…(2). The maximum delay time for the energy request at time slot t is 4). The upper bound of X(t) at any time slot t is −Φ max − b max ≤ X(t) ≤ b max , ∀t.…”

Section: Algorithm Performance Analysismentioning

confidence: 99%

“…However, in practice, their integration into the existing grid infrastructure must be carried out carefully in order to avoid instability and ensure availability and security of supply. The reason is that the high penetration levels of RESs can lead instability problems in the grid due to their limited predictability, controllability and variability [4]. To meet this challenge, numerous solutions for renewable energy generation forecasting have been proposed in the literature such as the hybrid of genetic algorithm and artificial neural networks [5], integration of wavelet transform, particle swarm optimization and support vector machines [6].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

et al. 2020

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In the smart grid, the end-users have the opportunity to integrate renewable energy sources (RESs) and participate in two-way energy trading. At the same time, an increasing number of flexible loads (FLs) have been developed for use on the demand side. Thus, this paper considers joint energy trading and load scheduling at a end-user with integrated renewable generation. With unknown statistics on renewable generation, loads and electricity prices, we aim at optimizing both energy trading and load scheduling to maximize the long-term average profit of the end-user, subject to load delay constraints. We employ the Lyapunov optimization theory to solve this stochastic problem with a series of problem corrections and transformations that enable us to design a dynamic energy trading and load scheduling algorithm. Within the performance analysis of the algorithm, we further demonstrate that the algorithm not only provides a bounded performance guarantee to the optimal solution that has complete future information, but is also asymptotically equivalent to it as the battery capacity or the delay time of FLs tend to infinity. The simulation results show that the proposed algorithm is superior to other algorithms both in terms of performance and service delay. Moreover, we can achieve a trade-off between comfort and total profit by adjusting the values of the parameters, and analyze the effect of battery capacity on algorithm performance to provide a theoretical basis for the end-user to determine battery capacity.INDEX TERMS Smart grid, renewable energy sources, energy trading, flexible loads, load scheduling.

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“…(2). The maximum delay time for the energy request at time slot t is 4). The upper bound of X(t) at any time slot t is −Φ max − b max ≤ X(t) ≤ b max , ∀t.…”

Section: Algorithm Performance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

et al. 2020

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“…Also the huge development potential of wind power is being discovered. 5,6 Wind power, as an important renewable energy source, makes a great contribution to energy conservation and emission reduction. However, as more wind power is introduced into the power system, greater frequency deviation also appears.…”

Section: Introductionmentioning

confidence: 99%

Dynamic event-triggered H_∞ quantized load frequency control for interconnected wind power systems under stochastic delay deception attack

Zhou

Zhong

et al. 2023

Sustainable Energy Fuels

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“…In order to achieve the aim of energy conservation and emission reduction, a large amount of RE has been incorporated into IES [9]. The large-scale incorporation of RE is beneficial to the development of IES, and IES is also characterized by its ability to integrate a large amount of RE [10].…”

Section: Introductionmentioning

confidence: 99%

Two-Stage Scheduling Strategy for Integrated Energy Systems Considering Renewable Energy Consumption

Liu¹,

Xie²,

Tian³

et al. 2022

IEEE Access

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With the crisis of energy and environment, the integrated energy systems (IES) have a bright prospect in future energy reform owing to the excellent economic and environmental performance. The IES combines a large amount of renewable energy (RE), which guarantees its economic and environmental benefits. Many uncertainties of RE threaten the performance of IES. How to promote RE consumption under strong uncertainties is a crucial problem in the scheduling of IES. In this work, a two-stage scheduling strategy for IES combining day-ahead scheduling and real-time scheduling is proposed to guide the system operation. The stage of day-ahead scheduling can obtain the optimal scheduling scheme one day in advance based on the forecast data of RE, and the stage of real-time scheduling is introduced to cope with the uncertainties of RE. The model of IES is established based on the energy hub (EH), and the entire strategy is implemented on this model. The model integrates various energy conversion equipment to give full play to the advantages of coordination and complementation of IES. The improved particle swarm optimization (IPSO) is proposed as the solution algorithm of the whole strategy, which improves the traditional PSO through random nonlinearity change inertia weight strategy and best solution perturbation operator (BSPO). Compared with the traditional PSO, IPSO has more excellent performance for solving IES scheduling model. Finally, different schemes under different situations are compared.

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Grid-Specific Co-Optimization of Incentive for Generation Planning in Power Systems With Renewable Energy Sources

Cited by 31 publications

References 25 publications

Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

Dynamic event-triggered H_∞ quantized load frequency control for interconnected wind power systems under stochastic delay deception attack

Two-Stage Scheduling Strategy for Integrated Energy Systems Considering Renewable Energy Consumption

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Grid-Specific Co-Optimization of Incentive for Generation Planning in Power Systems With Renewable Energy Sources

Cited by 31 publications

References 25 publications

Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

Dynamic Energy Trading and Load Scheduling Algorithm for the End-User in Smart Grid

Dynamic event-triggered H∞ quantized load frequency control for interconnected wind power systems under stochastic delay deception attack

Two-Stage Scheduling Strategy for Integrated Energy Systems Considering Renewable Energy Consumption

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Product

Resources

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Dynamic event-triggered H_∞ quantized load frequency control for interconnected wind power systems under stochastic delay deception attack