Optimal Allocation of Clean Energy in Terms of Probabilistic Multi-Objective Optimization Method

Abstract

In this paper, the Probabilistic Multi-Objective Optimization method (PMOO) is applied to perform the optimal allocation of clean energy with multiple objectives. A solar photo-thermal system, wind energy, and a comprehensive energy storage system for photo-thermal power generation are involved. In PMOO, a new concept of "preferable probability" is put forward to address the preference degree of an attribute of a candidate and the corresponding evaluation method and attributes of the alternative scheme are divided into two types, i.e., beneficial type and unbeneficial (cost) type of attributes, and the corresponding evaluation algorithms of their partial preferable probability are formulated quantitatively. The total preferable probability of each alternative scheme is the product of all possible partial preferable probability, which is employed as the unique indicator to conduct the ranking of the optimization. In the application of optimum allocation problem of clean energy, the solar energy assurance rate and efficiency index of the heating system are the optimal criteria to be maximized, while the heat collecting area of solar collector, the heating capacity of heat pump and the volume of water tank for heat storage are used as input parameters. Especially, the range analysis of the total preferable probability of each alternative scheme is conducted using orthogonal experimental design. The result indicates the optimum configuration for this allocation of clean energy design. Alternatively, in the application of wind-photo-thermal power generation and storage comprehensive energy system problem, both carbon emissions and total operating costs are the optimization criteria to be minimized for the three scenarios, yielding an optimal configuration.