System planning to achieve automation of network operation and reduction of operation costs

In the management of the nuclear combustible life-cycle, periodic shutdowns are necessary to replace and rearrange fuel elements in the core. During the weeks of maintenance other sources are used to supply the energy gap, typically at higher costs. However, in systems with large integration of renewable energy sources, where the energy availability and costs are seasonal, the shutdown schedule may play an important role in the system costs. Thus, this paper evaluates the impact of a nuclear power plant fuel replacement in the system operation, mainly in the supply of electricity and its costs. A part of the Brazilian southeast hydroelectric system was used to illustrate the impact of the shutdown scheduling and how the system planning can minimize its operation costs. The system operation costs were lower with the shutdown scheduled during the season with large availability of energy resources. However, in Brazilian hydro-dominated power system, this cost variation can be partially compensated by the modification the hydroelectric operation.

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An Interval Optimization-Based Approach for Electric–Heat–Gas Coupled Energy System Planning Considering the Correlation between Uncertainties

Energies ◽

10.3390/en14092457 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2457

Author(s):

Wenshi Wang ◽

Houqi Dong ◽

Yangfan Luo ◽

Changhao Zhang ◽

Bo Zeng ◽

...

Keyword(s):

Demand Response ◽

Energy System ◽

Interval Order ◽

Interval Optimization ◽

System Planning ◽

Energy Hub ◽

Operation Costs ◽

Integrated Energy System ◽

Electric Heat ◽

Energy System Planning

In this paper, a novel methodological framework for energy hub (EH) planning, considering the correlation between renewable energy source (RES) and demand response (DR) uncertainties, is proposed. Unlike other existing works, our study explicitly considers the potential correlation between the uncertainty of integrated energy system operations (i.e., wind speed, light intensity, and demand response). Firstly, an EH single-objective interval optimization model is established, which aims at minimizing investment and operation costs. The model fully considers the correlation between various uncertain parameters. Secondly, the correlation between uncertainties is dealt with by the interval models of multidimensional parallelism and affine coordinate transformation, which are transformed into a deterministic optimization problem by the interval order relationship and probability algorithm, and then solved by a genetic algorithm. Finally, an experimental case is analyzed, and the results show that the research method in this paper has good engineering practicability. At the same time, different correlations among uncertainties have different influences on integrated energy system planning. Correlation and influence are positively correlated.

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