Multi-time scale coordinated optimal dispatch of microgrid cluster based on MAS

Chen, Lijuan; Zhu, Xu; Cai, Jianguo; Xu, Xiaohui; Liu, Haixuan

doi:10.1016/j.epsr.2019.105976

Cited by 35 publications

(23 citation statements)

References 12 publications

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“…(4) The active power output of each generator is calculated by using (15), and then it is limited according to (16). (5) When the necessary condition (12) is satisfied after several iterations, the optimal allocated power for each generator is P g, i opt = P g, i (λ 0 ).…”

Section: Distributed Ed Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Real‐time distributed economic dispatch scheme of grid‐connected microgrid considering cyberattacks

Huang

Wang

Deng

et al. 2020

IET Renewable Power Generation

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Section: Distributed Ed Algorithmmentioning

confidence: 99%

“…], energy storages (ESs) and loads [1,2]. The microgrid can achieve the complementarity of different energy sources, reduce the operational cost, enhance the energy efficiency and improve the reliability of electricity supply [3][4][5]. Generally, the microgrid can operate either in islanded mode or in grid-connected mode.…”

Section: Introductionmentioning

confidence: 99%

Real‐time distributed economic dispatch scheme of grid‐connected microgrid considering cyberattacks

Huang

Wang

Deng

et al. 2020

IET Renewable Power Generation

View full text Add to dashboard Cite

“…Chen et al [30] developed a scheduling model based on multi-agent system for the coordination of multiple MGs. Such coordination is carried out by means of the alternating direction method of multipliers, obtaining the optimal energy management of the multiple MGs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Considering a determined individual i, the value of its objective function (O (i,k) ) during a determined iteration (k), which has to be minimized, is calculated according to (30):…”

Section: Problem Formulationmentioning

confidence: 99%

Day-Ahead Optimal Battery Operation in Islanded Hybrid Energy Systems and Its Impact on Greenhouse Gas Emissions

et al. 2019

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This paper proposes a management strategy for the daily operation of an isolated hybrid energy system (HES) using heuristic techniques. Incorporation of heuristic techniques to the optimal scheduling in day-head basis allows us to consider the complex characteristics of a specific battery energy storage system (BESS) and the associated electronic converter efficiency. The proposed approach can determine the discharging time to perform the load peak-shaving in an appropriate manner. A recently proposed version of binary particle swarm optimization (BPSO), which incorporates a time-varying mirrored S-shaped (TVMS) transfer function, is proposed for day-ahead scheduling determination. Day-ahead operation and greenhouse gas (GHG) emissions are studied through different operating conditions. The complexity of the optimization problem depends on the available wind resource and its relationship with load profile. In this regard, TVMS-BPSO has important capabilities for global exploration and local exploitation, which makes it a powerful technique able to provide a high-quality solution comparable to that obtained from a genetic algorithm.Incorporation of ESS can improve the accommodation of renewable generation while reducing greenhouse gas (GHG) emissions. As an example, incorporation of renewable power combined with ESS in California could reduce carbon dioxide (CO 2 ) emissions from 90% to 72%, whereas renewable power curtailment reduces from 33% to 9%. In the case of Texas, CO 2 emissions could be reduced from 58% to 54% and renewable power curtailment could be reduced from 3% to 0.3% [4]. Combination of carbon capture and storage devices with conventional generation units is also an option to reduce GHG emissions. However, the combination of renewable generation with ESS can be energetically more effective [5].Historically, the acquisition costs of a battery energy storage system (BESS) have been considerably high, limiting their economic performance and consequently their mass adoption. However, when very low GHG emissions are required, BESS can be a critical device to achieve such an ambitious goal.In the case of energy provision for an isolated hybrid energy system (HES), incorporation of BESS becomes profitable due to the fact that the fuel consumption and operating hours of a conventional generator are considerably reduced. In the case of a grid-connected HES, retailing rates and feed-in tariffs as well as favorable resources are crucial for their successful adoption [6].Heuristic techniques are commonly used to carry out the optimal sizing of a specific HES. Consequently, some of them have been implemented in computational programs such as HOMER Pro ® [7], iHOGA ® [8], and Hybrid2 ® [9], among others. Dispatch strategies implemented in most of these tools are based on load following and cycle charging concepts. Load following consists of generating power from conventional units only to satisfy net load (NL), and this approach is frequently suggested in a HES with high share of renewable power, which is much h...

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“…In view of this, the authors of [10] established the intra-day rolling scheduling model and adopted the intra-day rolling scheduling to modify the day-ahead plan output. In [11], through day-ahead scheduling, day-in rolling, and real-time dispatch, the influence of uncertain factors on microgrid cluster's stable and economic operation could be eliminated to the most extent; whereas, in the above literatures, the impact of initial heat storage capacity of the HSD on the optimization results was not discussed, and most of them assigned a fixed value such as the total or half capacity of the HSD. Furthermore, the operation optimization of HSD is a typical multi-stage decision problem, with close relationship between different periods, but the intra-day scheduling plan cannot be globally optimized because it is a phased plan (four hours), whereas the wind power uncertainty model used in most of the current researches did not consider the temporal dependence of wind power fluctuation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method

Zhou

Guo

et al. 2020

Energies

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The wind–heat conflict and wind power uncertainty are the main factors leading to the phenomenon of wind curtailment during the heating period in the northern region of China. In this paper, a multi-time scale optimal scheduling strategy for combined heat and power system is proposed. Considering the temporal dependence of wind power fluctuation, the intra-day wind power scenario generation method is put forward, and both day-ahead and intra-day optimization scheduling models based on the scenario method are established to maximize the system’s revenue. The case analyzes the impacts of the initial heat storage capacity of a heat storage device and different scheduling strategies on system revenue. It is verified that the scheduling strategy can better adapt to wind power uncertainty and improve the absorption capacity of wind power, while ensuring the safety and economical efficiency of system operation.

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Multi-time scale coordinated optimal dispatch of microgrid cluster based on MAS

Cited by 35 publications

References 12 publications

Real‐time distributed economic dispatch scheme of grid‐connected microgrid considering cyberattacks

Real‐time distributed economic dispatch scheme of grid‐connected microgrid considering cyberattacks

Day-Ahead Optimal Battery Operation in Islanded Hybrid Energy Systems and Its Impact on Greenhouse Gas Emissions

Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method

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