A Novel Multi-Agent DDQN-AD Method-Based Distributed Strategy for Automatic Generation Control of Integrated Energy Systems

Xi, Lei; Lü, Yu; Xu, Yanchun; Wang, Shouxiang; Chen, Xi

doi:10.1109/tste.2019.2958361

Cited by 103 publications

(41 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to optimize the power supply of photovoltaic microgrid composed of more partially shaded photovoltaic power modules, a control strategy with global maximum power tracking is required [8], [9]. Since photovoltaic cells initially generate direct current, generally multiple photovoltaic power sources form a direct current photovoltaic microgrid [10].…”

Section: The Output Characteristics Of Photovoltaic Power Supply Under Partial Shadow and The Structure Of Microgridmentioning

confidence: 99%

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

et al. 2021

View full text Add to dashboard Cite

There are some problems in the photovoltaic microgrid system due to the solar irradiancechange environment, such as power fluctuation, which leads to larger power imbalance and affects the stable operation of the microgrid. Aiming at the problems of power mismatch loss under partial shading in photovoltaic microgrid systems, this paper proposed a distributed maximum power point tracking (DMPPT) approach based on an improved sparrow search algorithm (ISSA). First, used the center of gravity reverse learning mechanism to initialize the population, so that the population has a better spatial solution distribution; Secondly, the learning coefficient was introduced in the location update part of the discoverer to improve the global search ability of the algorithm; Simultaneously used the mutation operator to improve the position update of the joiner and avoid the algorithm falling into the local extreme value. The results of the model in Matlab showed that the ISSA can track the maximum power point(MPP) more accurately and quickly than the perturbation observation method (P&O) and the particle swarm optimization (PSO) algorithm, and had good steady-state performance.INDEX TERMS Distributed maximum power point tracking, photovoltaic microgrid, sparrow search algorithm, spatial solution distribution, steady-state.

show abstract

Section: The Output Characteristics Of Photovoltaic Power Supply Under Partial Shadow and The Structure Of Microgridmentioning

confidence: 99%

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In this paper, the interaction mechanism is limited to among DSO and EVAs. Designing a bilevel game which accounts the interests of DSO, EVA and EV owners and its own solution method or artificial intelligence method [34] are the focus in future study.…”

Section: ⅵ Conclusionmentioning

confidence: 99%

Real-Time Optimal Scheduling of Large-Scale Electric Vehicles: A Dynamic Non-Cooperative Game Approach

Chen

et al. 2020

IEEE Access

View full text Add to dashboard Cite

In the presence of the increasing penetration of electric vehicles (EVs) and conflict of independent optimization objectives among each electric vehicle aggregator (EVA), real-time optimal scheduling (RTOS) of large-scale EVs based on dynamic non-cooperative game approach is proposed for optimal decision makings in a dynamic pricing market. First, real-time optimal scheduling framework is designed to describe the flow of energy and information. Then, equivalent model of large-scale EVs is formulated to address "curse of dimensionality" caused by a large number of decision variables. Then, the potential game theory is used to study the existence and uniqueness of the Nash equilibrium (NE) solution. Finally, a distributed approach based on alternating direction method of multipliers (ADMM) is designed to achieve the equilibrium. Case studies demonstrate that the proposed approach achieves peak load shifting and reduces cost of EVAs significantly. Furthermore, the proposed method obtains higher-quality solution compared with other methods and is more applicable for real-time optimal scheduling of large-scale EVs due to its high computation efficiency and privacy protection. INDEX TERMS Large-scale electric vehicles; real-time optimal scheduling; dynamic non-cooperative game; distributed optimization.

show abstract

“…For example, in some works, variance reduction techniques [17][18][19] are adopted to accelerate convergence speed and improve calculation efficiency of Monte Carlo based simulation, among which control variable (CV) [20], [21], average-and-scattered sampling (ASS) [22], importance sampling (IS) [23], antithetic variable (AV) [24] are commonly adopted. The ASS is adopted in reference [25] to reduce variance by averaging the experimental function in each interval (gotten by evenly dividing the interval [0, 1]) of each sampling as the new experimental function of the system. Since there are no restriction conditions for applying ASS, it is suitable for combining with other variance reduction techniques owing to its strong applicability.…”

Section: Introductionmentioning

confidence: 99%

A Pseudo-Analytical Mix Sampling Strategy for Reliability Assessment of Power Girds

Wei

Qiu³

et al. 2021

IEEE Access

Self Cite

View full text Add to dashboard Cite

A Novel Multi-Agent DDQN-AD Method-Based Distributed Strategy for Automatic Generation Control of Integrated Energy Systems

Cited by 103 publications

References 28 publications

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

Real-Time Optimal Scheduling of Large-Scale Electric Vehicles: A Dynamic Non-Cooperative Game Approach

A Pseudo-Analytical Mix Sampling Strategy for Reliability Assessment of Power Girds

Contact Info

Product

Resources

About