Open Access

ARTICLE

Sustainability Evaluation of Modern Photovoltaic Agriculture Based on Interval Type-2 Fuzzy AHP-TOPSIS and Least Squares Support Vector Machine Optimized by Fireworks Algorithm

Yi Liang^1,2, Haichao Wang^3,*, Wei-Chiang Hong⁴

1 School of Management, Hebei GEO University, Shijiazhuang, 050031, China
2 Strategy and Management Base of Mineral Resources in Hebei Province, Hebei GEO University, Shijiazhuang, 050031, China
3 Long Yuan (Beijing) Wind Power Engineering & Consulting Co., Ltd., Beijing, 100034, China
4 Department of Information Management, Oriental Institute of Technology, New Taipei, Taiwan

* Corresponding Author: Haichao Wang. Email:

(This article belongs to the Special Issue: Renewable Energy Development under Climate Change)

Energy Engineering 2022, 119(1), 163-188. https://doi.org/10.32604/EE.2022.017396

Received 07 May 2021; Accepted 05 August 2021; Issue published 22 November 2021

Abstract

Photovoltaics (PV) has been combined with many other industries, such as agriculture. But there are many problems for the sustainability of PV agriculture. Timely and accurate sustainability evaluation of modern photovoltaic agriculture is of great significance for accelerating the sustainable development of modern photovoltaic agriculture. In order to improve the timeliness and accuracy of evaluation, this paper proposes an evaluation model based on interval type-2 Fuzzy AHP-TOPSIS and least squares support vector machine optimized by fireworks algorithm. Firstly, the criteria system of modern photovoltaic agriculture sustainability is constructed from three dimensions including technology sustainability, economic sustainability and social sustainability. Then, analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) methods are improved by using interval type-2 fuzzy theory, and the traditional evaluation model based on interval type-2 Fuzzy AHP-TOPSIS is obtained, and the improved model is used for comprehensive evaluation. After that, the optimal parameters of least squares support vector machine (LSSVM) model are obtained by Fireworks algorithm (FWA) training, and the intelligent evaluation model for the sustainability of modern photovoltaic agriculture is constructed to realize fast and intelligent calculation. Finally, an empirical analysis is conducted to demonstrate the scientificity and accuracy of the proposed model. This study is conducive to the comprehensive evaluation of the sustainability of modern photovoltaic agriculture, and can provide decision-making support for more reasonable development model in the future of modern photovoltaic agriculture.

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