A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China

Using agricultural straw to generate electricity is an effective approach for relieving the pressure of procuring a reliable energy supply and reducing environmental pollution. Because the locations of the power plants have a significant impact on the supply of raw materials and the cost of transportation, it is important to choose reasonable locations for power plants. To solve the problem of straw-based power plant site selection (SPPSS), in this paper, a spatially explicit optimization model is proposed. Compared to the existing research, the present study makes the following major contributions: (1) The agricultural land quality evaluation dataset, combined with the cropping system and theoretical yield information, is used as the basic data to estimate agricultural straw yields, thereby increasing the accuracy of the straw yield and spatial distribution estimates. (2) Geographic information system (GIS) techniques are employed to improve an artificial immune system (AIS), which is an effective and flexible approach for solving optimization problems. The Chinese province of Hubei is selected as the experimental area to evaluate the effectiveness of the proposed model. The experimental results demonstrate that of the 34.89 million tons of agricultural straw produced in Hubei Province each year, 17.45 million tons can be used for electricity generation. The optimization schemes generated by the proposed model are feasible. Our results are expected to provide an important decision-making basis for straw-based power plant (SPP) development planning in Hubei Province.