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Challenges of Renewable Forest Fuels for Green Electricity Market

机译:可再生森林燃料对绿色电力市场的挑战

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In this study, strategic electricity market scenarios are considered in a grid of Scandinavia. This multiple-objective decision environment includes the allocation of a number of renewable forest fuel procurement chains to a combined heat and power plant in Finland. The decision environment includes also electricity procurement from Sweden and Russia. The environment is further complicated by sequence-dependent operations of the local procurement chains during different periods. Due to the complex nature of the environment, multiple-objective methods cannot be directly used to solve the electricity production problem in a manner that is techno-economically relevant to the forest energy industry. Therefore, local and time-varying parameters were measured in local wood procurement conditions to improve the solution method. Using these measurements the smart decision-support system automatically adjusted the multiple-objective methodology to better describe the combinatorial complexity of the production sector. The properties of this methodology are discussed and three scenarios of how the system works based on local real-world data and optional feed-in tariff of green electricity are presented. The Finnish electricity market is subject to policy decisions regarding green energy production regulations. These decisions should be made on the basis of local techno-economic analysis presented in this study accounting for the effects of forest operations on the electricity production and import.
机译:在这项研究中,在斯堪的纳维亚半岛的电网中考虑了战略性电力市场情景。这种多目标决策环境包括将许多可再生森林燃料采购链分配给芬兰的热电厂。决策环境还包括从瑞典和俄罗斯采购电力。在不同时期,当地采购链的依序运行会进一步使环境复杂化。由于环境的复杂性,多目标方法不能以与森林能源行业在技术经济上相关的方式直接用于解决电力生产问题。因此,在当地木材采购条件下测量了局部和时变参数,以改进求解方法。使用这些度量,智能决策支持系统会自动调整多目标方法,以更好地描述生产部门的组合复杂性。讨论了该方法的特性,并提出了三种基于本地实际数据和可选的绿色上网电价的系统工作方式的方案。芬兰电力市场受有关绿色能源生产法规的政策决定的约束。这些决定应基于本研究中提出的当地技术经济分析来做出,其中应说明森林经营对电力生产和进口的影响。

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