An optimization model for multi-biomass tri-generation energy supply

Abstract

In this paper, a decision support system (DSS) for multi-biomass energy conversion applications is presented. The system in question aims at supporting an investor by thoroughly assessing an investment in locally existing multi-biomass exploitation for tri-generation applications (electricity, heating and cooling), in a given area. The approach followed combines use of holistic modelling of the system, including the multi-biomass supply chain, the energy conversion facility and the district heating and cooling network, with optimization of the major investment-related variables to maximize the financial yield of the investment. The consideration of multi-biomass supply chain presents significant potential for cost reduction, by allowing spreading of capital costs and reducing warehousing requirements, especially when seasonal biomass types are concerned. The investment variables concern the location of the bioenergy exploitation facility and its sizing, as well as the types of biomass to be procured, the respective quantities and the maximum collection distance for each type. A hybrid optimization method is employed to overcome the inherent limitations of every single method. The system is demand-driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of an investor to assess and optimize in financial terms an investment aiming at covering real energy demand. optimization is performed taking into account various technical, regulatory, social and logical constraints. The model characteristics and advantages are highlighted through a case study applied to a municipality of Thessaly, Greece. (C) 2008 Elsevier Ltd. All rights reserved

Managing the moisture content of wood biomass for the optimisation of Ireland's transport supply strategy to bioenergy markets and competing industries

“…Biomass resources are also often distributed in remote locations (Lam et al 2010). These factors add complexities to the supply chain and can increase the cost of the technology required to convert biomass into useful sources of energy (harvesting, collection, transport, comminution and storage operations) (Rentizelas et al 2009). The current costs of primary biomass fuels are also often higher than the cost of competing fossil fuels (Junginger et al 2005).…”

“…Recent advances in computational tools have made possible to build mathematical models for analysis and optimisation of complex supply systems (Azadeh et al 2014). Many approaches have been used to simulate and optimise specific biomass supply chains, to get a better understanding of the cost reductions that could result from the implementation of more efficient logistics operations while ensuring a reliable and sustainable supply of forest fuel (Rentizelas et al 2009). …”

Optimisation and investment analysis of two biomass-to-heat supply chain structures

“…The concept of the exploitation of multiple biomass feedstocks has recently emerged, providing interesting alternatives to conventional single-biomass sourcing strategies (Rentizelas et al 2009a, Rentizelas et al 2009b. Apart from the logistical analysis, the aforementioned studies investigated the need for optimizing the entire supply chain and the location of bioenergy facilities, using complex optimization algorithms.…”

“…The multi-fuel concept is adapted from the multi-biomass model of Rentizelas et al (2009a). The model presented in Rentizelas et al (2009a) has been adapted and used for the case of the CHP plant.…”

A hybrid optimization model of biomass trigeneration system combined with pit thermal energy storage

“…At the same time, using biomass as a fuel for the trigeneration power plant increases the renewable energy share in the overall production mix. Rentizelas et al [4] provide an optimization model for energy supply based on multibiomass trigeneration, covering peak demand with a biomass boiler. Puig-Arnavat et al [5] assessed different trigeneration configurations based on biomass gasification.…”