Multiobjective robust fuzzy stochastic approach for sustainable smart grid design

Tsao, Yu‐Chung; Thanh, Vo-Van; Lu, Jye‐Chyi

doi:10.1016/j.energy.2019.04.047

Cited by 36 publications

(13 citation statements)

References 29 publications

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“…The energy demand is assumed to be dependent on electricity price when developing the demand response programs for energy efficiency goals [ 20 ]. However, energy is a primary and essential need for life.…”

Section: Problem Definition and Model Formulationmentioning

confidence: 99%

“…This demand function enables us to capture that consumers are sensitive to both energy prices and COVID-19, where the price elasticity coefficient of energy demand ( τ ) is set based on Ref. [ 20 ] and the effects of COVID-19 on energy demand ( β ) is an uncertain parameter. Because the COVID-19 effects on energy supply and demand are assumed to be independent and uncertain parameters, the value of parameter β is not affected by various conditions of elasticity.…”

Section: Problem Definition and Model Formulationmentioning

confidence: 99%

“…The COVID-19 pandemic is considered a risk event that has affected all aspects of life and led to critical network disruptions. Several previous studies have developed uncertain programming models to overcome the uncertainty in parameters and risks in the power system planning field with or without government subsidies [ [20] , [21] , [22] , [23] , [24] , [25] , [26] ]. For example, Tsao el al.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Tsao el al. [ 20 ] applied an integrated approach to deal with hybrid fuzzy-stochastic vagueness in smart electricity distribution networks. The applied model can cope with both operational and disruption risks to enhance the sustainability of the intelligent grid.…”

Section: Introductionmentioning

confidence: 99%

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COVID-19: Government subsidy models for sustainable energy supply with disruption risks

Tsao

Thanh

Chang

et al. 2021

Renewable and Sustainable Energy Reviews

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The outbreak of the COVID-19 pandemic poses great challenges to the current government subsidy models in the renewable energy sector for recovering in the post-pandemic economy. Although, many subsidy models have been applied to accelerate renewable energy investment decisions. However, it is important to develop a new model to ensure the sustainability of the renewable energy supply network under disruptions on both the supply and demand sides due to hazardous events. This study investigates different subsidy models (renewable credit, supplier subsidy, and retailer subsidy) to find a win-win subsidy model for sustainable energy supply under disruption risks. The objective is to determine the optimal capacity of renewable energy added to the grid, the optimal wholesale price of the power plant, and the optimal retail price of the aggregator under different subsidy models to maximize the economic, social, and environmental benefits of the whole network. A novel scenario-based robust fuzzy optimization approach is proposed to capture the uncertainties of business-as-usual operations (e.g., some relevant costs and demand) and hazardous events (e.g., COVID-19 pandemic). The proposed model is tested in a case study of the Vietnamese energy market. The results show that for a high negative impact level of hazardous events on the supply side, the renewable credit and supplier subsidy models should be considered to recovery the renewable energy market. Further, the proposed approach has a better performance in improving the power plant's robust profit for most of the hazard scenarios than the robust optimization model.

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Section: Problem Definition and Model Formulationmentioning

confidence: 99%

Section: Problem Definition and Model Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

COVID-19: Government subsidy models for sustainable energy supply with disruption risks

Tsao

Thanh

Chang

et al. 2021

Renewable and Sustainable Energy Reviews

Self Cite

View full text Add to dashboard Cite

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“…The optimal solution sets of robust optimization have a certain degree of restraint on the effects. Adjusting the size of a coefficient can determine the dispatching scheme, which can restrain the influence of uncertainty to different degrees [17]. At the same time, the existing research results are more focused on the processing of constraints with uncertain variables, lacking consideration of the objective function processing method with uncertain variables.…”

Section: Introductionmentioning

confidence: 99%

A Risk Aversion Dispatching Optimal Model for a Micro Energy Grid Integrating Intermittent Renewable Energy and Considering Carbon Emissions and Demand Response

Fan

Lin

et al. 2019

Processes

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This paper focuses on an optimal schedule for a micro energy grid considering the maximum total carbon emission allowance (MTEA). Firstly, the paper builds an energy devices operation model and demand response (DR) model. Secondly, to maximize the economical operation revenue, the basic scheduling model for the micro energy grid is constructed. Thirdly, the conditional value at risk method and robust stochastic theory are introduced to describe the uncertainty of wind power, photovoltaic power, and load, and a risk aversion model is proposed. Finally, this paper selects the Xinxiang active distribution network demonstration project in Jining, China as an example. The results show that: (1) a micro energy grid can make the most use of the complementary characters of different energy sources to meet different energy demands for electricity, heat, cold, and gas; (2) the risk aversion scheduling model can represent the influence of uncertainty variables in objective functions and constraints, and provide a basis for decision makers who have different attitudes; and (3) DR can smooth the energy load curves. MTEA can enhance the competitiveness of the clean energy market, thus promoting the grid-connected generation of clean energy. Therefore, the risk aversion model can maximize the economic benefits and provide a basis for decision makers while rationally controlling risks.

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A bibliometric review on the application of fuzzy optimization to sustainable energy technologies

Arriola

Ubando

Chen

2020

Intl J of Energy Research

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Multiobjective robust fuzzy stochastic approach for sustainable smart grid design

Cited by 36 publications

References 29 publications

COVID-19: Government subsidy models for sustainable energy supply with disruption risks

COVID-19: Government subsidy models for sustainable energy supply with disruption risks

A Risk Aversion Dispatching Optimal Model for a Micro Energy Grid Integrating Intermittent Renewable Energy and Considering Carbon Emissions and Demand Response

A bibliometric review on the application of fuzzy optimization to sustainable energy technologies

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