{"title":"Optimization of biogas supply networks considering multiple objectives and auction trading prices of electricity","authors":"Jafaru Musa Egieya, Lidija Čuček, Klavdija Zirngast, Adeniyi Jide Isafiade, Zdravko Kravanja","doi":"10.1186/s42480-019-0025-5","DOIUrl":null,"url":null,"abstract":"<p>This contribution presents an hourly-based optimization of a biogas supply network to generate electricity, heat and organic fertilizer while considering multiple objectives and auction trading prices of electricity. The optimization model is formulated as a mixed-integer linear programming (MILP) utilizing a four-layer biogas supply chain. The model accounts for biogas plants based on two capacity levels of methane to produce on average 1?±?0.1?MW and 5?±?0.2?MW electricity. Three objectives are put forward: i) maximization of economic profit, ii) maximization of economic profit while considering cost/benefits from greenhouse gas (GHG) emissions (economic<sup>+GHG</sup> profit) and iii) maximization of sustainability profit. The results show that the economic profit accrued on hourly-based auction trading prices is negative (loss), hence, four additional scenarios are put forward: i) a scenario whereby carbon prices are steadily increased to the prevalent eco-costs/eco-benefits of global warming; ii) a scenario whereby all the electricity auction trading prices are multiplied by certain factors to find the profitability breakeven factor, iii) a scenario whereby shorter time periods are applied, and investment cost of biogas storage is reduced showing a relationship between cost, volume of biogas stored and the variations in electricity production and (iv) a scenario whereby the capacity of the biogas plant is varied from 1?MW and 5?MW as it affects economics of the process. The models are applied to an illustrative case study of agricultural biogas plants in Slovenia where a maximum of three biogas plants could be selected. The results hence present the effects of the simultaneous relationship of economic profit, economic<sup>+GHG</sup> profit and sustainability profit on the supply and its benefit to decision-making.</p>","PeriodicalId":495,"journal":{"name":"BMC Chemical Engineering","volume":"2 1","pages":""},"PeriodicalIF":2.3500,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s42480-019-0025-5","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Chemical Engineering","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1186/s42480-019-0025-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This contribution presents an hourly-based optimization of a biogas supply network to generate electricity, heat and organic fertilizer while considering multiple objectives and auction trading prices of electricity. The optimization model is formulated as a mixed-integer linear programming (MILP) utilizing a four-layer biogas supply chain. The model accounts for biogas plants based on two capacity levels of methane to produce on average 1?±?0.1?MW and 5?±?0.2?MW electricity. Three objectives are put forward: i) maximization of economic profit, ii) maximization of economic profit while considering cost/benefits from greenhouse gas (GHG) emissions (economic+GHG profit) and iii) maximization of sustainability profit. The results show that the economic profit accrued on hourly-based auction trading prices is negative (loss), hence, four additional scenarios are put forward: i) a scenario whereby carbon prices are steadily increased to the prevalent eco-costs/eco-benefits of global warming; ii) a scenario whereby all the electricity auction trading prices are multiplied by certain factors to find the profitability breakeven factor, iii) a scenario whereby shorter time periods are applied, and investment cost of biogas storage is reduced showing a relationship between cost, volume of biogas stored and the variations in electricity production and (iv) a scenario whereby the capacity of the biogas plant is varied from 1?MW and 5?MW as it affects economics of the process. The models are applied to an illustrative case study of agricultural biogas plants in Slovenia where a maximum of three biogas plants could be selected. The results hence present the effects of the simultaneous relationship of economic profit, economic+GHG profit and sustainability profit on the supply and its benefit to decision-making.