ALBERT

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ning Zhao, Fengqi You〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This article addresses the optimal design of waste-to-energy incentive policy for the dairy sector that aims to promote dairy farms’ adoption of on-farm anaerobic digesters and combined heat and power units to generate biomass-based energy. A modeling framework based on the single-leader-multiple-follower Stackelberg game is developed, where the government is the leader and the dairy farms are independent followers. The leader has two conflicting objectives, minimizing total government intervention, including total negative and positive cash flows of the government, and minimizing its unit cost on generating a target amount of bioelectricity. The government determines a bioenergy incentive policy consisting of subsidy on bioelectricity generation, refund of capital investment and dairy manure disposal fee, under a bioelectricity generation target. The dairy farms should react to the policy and maximize their net present values independently by making decisions on anaerobic digestion adoption and biogas-to-energy conversion technology selection. The problem is formulated as a multi-objective mixed-integer bilevel fractional program, and it is solved efficiently using a tailored global optimization algorithm which integrates a parametric algorithm and a projection-based reformulation and decomposition algorithm. A case study on hundreds of the largest dairy farms in New York State is presented to demonstrate the applicability of the proposed modeling framework and solution algorithm. Computational results show that incentive policies can effectively promote bioelectricity generation, and the refund of capital investment to a farm is 499% to 768% higher compared to the subsidy on bioelectricity generation. Additionally, the minimum government intervention to double the anaerobic-digestion-based bioelectricity generation is $11.8 million.〈/p〉〈/div〉 〈/div〉