A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Optimization in Grid-Interactive Buildings
This chapter proposes an optimal scheduling approach for multi-energy grids (MEGs) integrated with the grid-interactive buildings. To optimally coordinate the grid-interactive buildings and the MEGs, this chapter develops a bi-level optimization method. The MEGs operator is able to activate the heating demand response (HDR) from grid-interactive buildings, while the grid-interactive buildings can enjoy heating cost saving with the proposed bi-level optimization method. At the upper level, the MEG operator optimizes the heating sale price (HSP) to the buildings and the energy schedules by dispatching the multi-energy devices. In the lower level, in order to reduce consumers’ heating costs, indoor radiators’ water flow rates are optimally adjusted according to the HSPs. To efficiently solve the bi-level optimization problem, we reformulate the original problem as a mixed-integer linear programming (MILP). We also use the piecewise linearization method to treat the nonlinearity of constraints of the heating distribution network. Case study results demonstrate that the proposed method can optimally coordinate the grid-interactive buildings and the MEGs. Consequently, the flexibility of the grid-interactive buildings can be fully used in the optimization of the multi-energy grids. Moreover, the heating costs of the buildings can be significantly reduced with the proposed bi-level optimization method.
Optimization in Grid-Interactive Buildings
This chapter proposes an optimal scheduling approach for multi-energy grids (MEGs) integrated with the grid-interactive buildings. To optimally coordinate the grid-interactive buildings and the MEGs, this chapter develops a bi-level optimization method. The MEGs operator is able to activate the heating demand response (HDR) from grid-interactive buildings, while the grid-interactive buildings can enjoy heating cost saving with the proposed bi-level optimization method. At the upper level, the MEG operator optimizes the heating sale price (HSP) to the buildings and the energy schedules by dispatching the multi-energy devices. In the lower level, in order to reduce consumers’ heating costs, indoor radiators’ water flow rates are optimally adjusted according to the HSPs. To efficiently solve the bi-level optimization problem, we reformulate the original problem as a mixed-integer linear programming (MILP). We also use the piecewise linearization method to treat the nonlinearity of constraints of the heating distribution network. Case study results demonstrate that the proposed method can optimally coordinate the grid-interactive buildings and the MEGs. Consequently, the flexibility of the grid-interactive buildings can be fully used in the optimization of the multi-energy grids. Moreover, the heating costs of the buildings can be significantly reduced with the proposed bi-level optimization method.
Optimization in Grid-Interactive Buildings
stud. in Infrastructure & Control
Tomar, Anuradha (editor) / Nguyen, Phuong H. (editor) / Mishra, Sukumar (editor) / Jin, Xiaolong (author) / Yu, Xiaodan (author) / Lu, Yihan (author) / Jia, Hongjie (author) / Mu, Yunfei (author)
2022-05-10
20 pages
Article/Chapter (Book)
Electronic Resource
English
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