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• This study addresses the sustainable mircogrids design problem under competition. • Leveraging blockchain technology to provide the demand response programs. • Three sustainable objectives (economy, environment, and society) are considered. • A robust fuzzy multi-objective optimization approach is proposed. • The proposed model and solution approach are then applied to a case study in Vietnam. In recent years, rapidly increasing electric power demand and organizational concerns regarding social and environmental issues have resulted in significant attention being given to microgrids. However, sustainable microgrids that simultaneously address economic benefits and environmental and social issues have not been broadly explored by researches. This study addresses the sustainable microgrid design problem by leveraging blockchain technology to provide the real time-based demand response programs. Three sustainable objectives (economy, environment, and society) are formulated by a multi-objective mixed integer-linear programming model. A robust fuzzy multi-objective optimization approach is proposed to determine the optimal number, location, and capacity of renewable distributed generation units as well as the equilibrium supply and dynamic pricing decisions under uncertain demand, capacity, and economic, environmental, and social parameters. The proposed model and solution approach are then applied to a case study in Vietnam. We find that blockchain technology-based sustainable microgrid can result in a 1.68% and 2.61% increase of profitability and consumer satisfaction, respectively, and a 0.97% reduction of environmental impacts. [ABSTRACT FROM AUTHOR]

A sustainable and reliable power system is extremely important to ensure the prosperity of a country and its society. Traditional power systems are facing serious environmental and social issues while renewable energy systems possess low reliability due to the intermittent nature of energy sources. This paper addresses the sustainable and reliable power system design problem in an uncertain environment by using an approach called multi-objective fuzzy robust programming. The proposed approach, which is an integration of robust programming and two main branches of fuzzy programming (possibilistic and flexible programming), solves the presented multi-objective problem by simultaneously improving both sustainability and reliability, as well as by capturing uncertain factors. The objective is to determine the optimal number, location, capacity, and technology of the generation units as well as the electricity generated and transmitted through the network while minimizing the sustainability and reliability costs of the system. The proposed model considers uncertainties in the demand, the intermittent nature of renewable energy resources, and cost parameters. A case study in Vietnam was conducted to demonstrate the efficacy and efficiency of the proposed model. Results show that the proposed model improves the total cost of the power system, including sustainability and reliability costs, by approximately 4.2% and reduces the computational time by 20% compared to the scenario-based stochastic programming approach. Our findings also show that due to risk disruption, the reliability cost of the power system increases to 56.72% when more electric power is generated. • Design a power distribution network with uncertain parameters. • A multi-objective robust possibilistic flexible programming method is presented. • The objective is to minimize the economic costs and environmental and social impacts. • We applied the method to Vietnam's electric power distribution network. • A robust sensitivity analysis technique allows the decision makers to select a proper energy strategy. [ABSTRACT FROM AUTHOR]