Abstract
Starting from the perspective of the uncertainty of supply and demand, using the Copula function and fuzzy numbers a scenario generation method, considering the uncertainty of scenery, and a random fuzzy model of energy demand uncertainty are proposed. Then, through the energy flow direction and the energy supply, production, conversion, storage, and demand, a multi-objective model considering the economic and environmental protection of a park is constructed. Here, the park refers to a microgrid that gathers distributed energy such as wind and photovoltaics and has requirements for cooling, heat, and electricity at the same time. Next, combining the constraints of each link, the particle swarm algorithm is used to solve the model. Finally, an example is analyzed in a certain park. The results of the example show that, on the one hand, the proposed scenario generation method and fuzzy number method can reduce the uncertainty of supply and demand, effectively fitting the wind and photovoltaic output and various energy demands. On the other hand, considering the economy and environmental protection of the park at the same time, the configuration of energy storage equipment can not only improve the economy of the park, but also promote the consumption of renewable energy.
Highlights
The microgrid integrates distributed energy, which can realize the complementary utilization of renewable energy such as wind and solar energy and become an important means to promote the consumption of renewable energy [2]
Sustainability 2021, 13, 1320 uncertainty, the scenario generation method and robust optimization have been introduced to reduce the uncertainty of wind and photovoltaic output
In order to consider the economy and environmental protection of the system at the same time, a multiobjective multienergy complementary park scheduling optimization model was proposed with the largest benefit of the multienergy complementary park and the lowest rate of outsourced electricity to promote the consumption of renewable energy
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Sustainability 2021, 13, 1320 uncertainty, the scenario generation method and robust optimization have been introduced to reduce the uncertainty of wind and photovoltaic output. Based on the above research, this article first uses the Frank function in the Copula function to construct a wind-solar complementary joint-distribution function and uses the second-order Fourier fitting method to fit the energy demand, such as cooling, heating, and electricity, to generate a scenario of typical daily wind and solar output and energy demand to solve the problem of considering only one-sided uncertainty. In order to consider the economy and environmental protection of the system at the same time, a multiobjective multienergy complementary park scheduling optimization model was proposed with the largest benefit of the multienergy complementary park and the lowest rate of outsourced electricity to promote the consumption of renewable energy. From the economic and environmental protection aspects of the multienergy complementary park, this paper constructs the objective function pursued by the park to improve the park’s income, promote the consumption of renewable energy, and realize multienergy complementary optimal scheduling within the park
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