Search

Waste-to-energy (WtE) is one of the municipal solid waste (MSW) management pathways that can reduce waste volumes while recovering energy. There has been considerable focus on using MSW for energy production; however, there are few integrated assessments of the optimal location and scale of the conversion of MSW to energy. This research develops a novel framework that integrates the analysis of candidate sites for MSW gasification facilities using a geographical information system (GIS) through a multi-criterion decision-making (MCDM) model with a mixed-integer linear programming (MILP) model to determine optimal scale and location. The most suitable candidate locations were identified through a GIS-based location-allocation analysis. A MILP model integrated with GIS was then used to determine the minimum per-unit electricity production costs by optimizing the numbers, locations, and sizes of the proposed WtE and preprocessing facilities. The key inputs to the optimization model are actual road and railway transportation distances, WtE gasification and preprocessing facility capital and installation costs, operation and maintenance costs, gate fee and tipping fees (the fee for disposal of ash at the landfill), and the municipal guidelines. The proposed integrated framework was applied in a case study for Alberta, a western province in Canada. The results indicate that at a 10% rate of return, electricity production is cost-competitive with current electricity prices. The per-unit cost of electricity production (COEP) was found to be only 16.14 $/MWh when the gate fee was treated as a revenue component. The optimal plant location was in Edmonton and the optimum plant size was 175 MW. Sensitivity and uncertainty analysis was conducted to understand the critical input parameters that impact the COEP. The results indicate that the COEP is most sensitive to changes in tipping fees, plant efficiency, capital cost, discount rate, and transportation cost. The developed framework is critical for investment decisions and policy development, and it can be applied globally with adjustments to data and assumptions. [Display omitted] • A novel integrated GIS-based optimization model is developed for MSW supply chain. • A GIS-based MCDM model is used to identify the candidate sites for WtE facilities. • ArcGIS network analysis is used to determine actual transportation distances. • The per unit COEP, 16.14 $/MWh, is competitive with the market price. • The proposed framework optimizes WtE facility numbers, locations, and sizes. [ABSTRACT FROM AUTHOR]

This study explores the technical and economic potential of three Canadian biomass feedstocks (spruce, corn stover and wheat straw) to replace petro-diesel through the production of renewable diesel and gasoline via fast pyrolysis and hydroprocessing. A detailed data-intensive process and cost model for a 2000 dry t d−1 plant capacity for two scenarios (hydrogen production and hydrogen purchase) was developed using both experimental and published data. The authors analyzed the quality and quantity of bio-oil, which acts as an intermediate for renewable diesel, by performing fast pyrolysis experiments in a lab -scale fluidized bed reactor at temperatures of 400–520 °C and three particle size distributions. The production costs of renewable diesel are 0.98 $ L−1,1.11 $ L−1, 1.19 $ L−1, and 1.27 $ L−1 for the spruce hydrogen purchase, spruce hydrogen production, corn stover hydrogen production, and wheat straw hydrogen production scenarios, respectively. The net energy ratios (NERs) of the process, which is the ratio of the energy content of the output product to fossil fuel inputs, were calculated to be 2.16, 1.5, and 1.16 for spruce, corn stover, and wheat straw, respectively. The effects of byproduct selling price on renewable diesel cost were also investigated. As the results suggest, the yields of renewable diesel and gasoline depend on the amount of bio-oil produced through fast pyrolysis followed by the properties of biomass. From the sensitivity analysis, it is concluded that the cost of transportation fuel is most sensitive to bio-oil yield. As the NER for all three feedstocks is more than 1, it can be said that fast pyrolysis and hydroprocessing technology is energy sustainable. Finally, this pathway could be competitive with conventional transportation fuels if the revenue from the biochar can be generated. • Fast pyrolysis experiments were conducted for Canadian biomass feedstocks. • Process and cost models were developed for a 2000 t d−1 capacity fast pyrolysis and hydroprocessing unit. • The production cost of renewable diesel ranges from 0.98 to 1.27 $ L−1 • The effects of byproduct costs on renewable diesel cost were investigated. • A detailed sensitivity analysis and net energy ratios are presented. [ABSTRACT FROM AUTHOR]

The diversification of Canadian oil sands markets is imperative for the long-term economic growth of oil sands products. To ensure a competitive place in the global market, supply chain costs of oil sands must be as low as possible. This study conducts a comparative techno-economic analysis of potential pathways for the transportation of Canadian oil sands products (synthetic crude oil and diluted bitumen) to seaport destinations in the Asia-Pacific region. We developed data-intensive techno-economic models to estimate total supply chain costs from the production site in Alberta to ports in China, Japan, and India. Four pathways were developed using production (steam assisted gravity drainage), transportation (production-upgrader-port in Vancouver), upgrading, and shipping operations. A sensitivity analysis was conducted to identify cost ranges with their occurrence probability measures and evaluate the effect of key parameters for each stage of operation. Supply chain costs (C$ per barrel of bitumen) to China, Japan, and India are from 61–87, 60–86, and 62–90, respectively. Overall supply chain costs of dilbit (a blend of bitumen and diluent) and synthetic crude oil (SCO) are affected most by production and upgrading costs. The production and upgrading costs are influenced by capital cost, while pipeline lifetime and capacity highly impact transportation (pipeline) and shipping costs, respectively. The developed models can be used to predict total supply chain costs of different pathways in Canadian oil sand markets. [ABSTRACT FROM AUTHOR]

• TEA of hydrogen production via photocatalytic water splitting was conducted. • Four earth abundant, active and stable photocatalysts were selected. • The LCOH ranges from 4.15 to 9.8 USD per kg of H 2 produced. • Capital investment and labour costs contribute the most, 75% of the total cost. • The system was scaled from lab to facility to produce 5 tonnes of H 2 per day. Photocatalytic water splitting using solar radiation is among the promising H 2 technologies. Titanium dioxide (TiO 2)- and carbon nitride (g-C 3 N 4)-based photocatalysts are the most widely used photocatalytic materials given their activity under visible light and their abundance. Several attempts have been made to improve the photocatalytic performance of these materials in terms of activity level, life span, response to visible radiation, and stability. However, the economic viability of the large-scale deployment of these modifications is not well evaluated in the existing literature. This study develops a bottom-up techno-economic assessment framework to determine the H 2 production costs in four alternative pathways: TiO 2 nanorods, fluorine-doped carbon nitride quantum dot-embedded TiO 2 (CNF: TNRs/TiO 2), g-C 3 N 4 , and g-C 3 N 4 /BiOI composite. Sensitivity and uncertainty analyses were also conducted to understand the impact of input parameters on the hydrogen production cost. The levelized costs of hydrogen (LCOH) are 4.9 - 0.70 + 0.75 , 5.7 - 0.65 + 0.45 , 5.8 - 1.15 + 0.55 , a n d 7.8 - 0.95 + 0.45 USD per kg of H 2 produced for TNRs, CNF: TNRs, g-C 3 N 4 -S, and BiOI/g-C 3 N 4 -S, respectively. In every pathway, the largest contribution is from capital investment and labour costs; together they make up around 75 % of the total cost. Material cost accounts for 13–29 % of the overall cost. The developed information can help in making investment decisions and policy formulation. [ABSTRACT FROM AUTHOR]

This article addresses the global optimal design of multi-stage flash desalination processes. The mathematical formulation accounts for non-linear programming (NLP) based process models that are supplemented with the non-deterministic optimization algorithm. MSF-once through, -simple mixture (MSF-M) and -brine recycle (MSF-BR) process configurations have been evaluated for their optimality. While freshwater production cost has been set as the objective function for minimization, mass, energy and enthalpy balances with relevant supplementary equations constitute the equality constraints. Differential evolution algorithm (DE/rand/bin) was adopted to evaluate the global optimal solutions. Further, obtained solutions have been compared with those obtained with MATLAB optimization toolbox solvers such as SQP and MS-SQP. The global optimal solution corresponds to a variable value set of [2794.4 m 3 /h, 1.0499, 7.62 m, 3.359 kW/m 2 ∙ K, 3.297 kW/m 2 ∙ K, 3.042 kW/m 2 ∙ K and 22] for decision variables [ W M , R H , L T , U B , U R , U j , N R ] in the MSF-BR process to yield an optimal freshwater production cost of 1.0785 $/m 3 . Compared to the literature, the obtained global solution from DE is 2.31% better. Further, inequality constraint resolution has been excellent for DE but not other methods such as MS-SQP, SQP and DE-SQP. [ABSTRACT FROM AUTHOR]

Minimum production cost and optimum plant size are determined for pellet plants for three types of biomass feedstock – forest residue, agricultural residue, and energy crops. The life cycle cost from harvesting to the delivery of the pellets to the co-firing facility is evaluated. The cost varies from 95 to 105 $ t −1 for regular pellets and 146–156 $ t −1 for steam pretreated pellets. The difference in the cost of producing regular and steam pretreated pellets per unit energy is in the range of 2–3 $ GJ −1 . The economic optimum plant size (i.e., the size at which pellet production cost is minimum) is found to be 190 kt for regular pellet production and 250 kt for steam pretreated pellet. Sensitivity and uncertainty analyses were carried out to identify sensitivity parameters and effects of model error. [ABSTRACT FROM AUTHOR]

Biomass can be converted to coal-like products known as hydrochar or biochar. Raw biomass generally has high moisture content. Wet torrefaction has gained considerable interest recently because of the unique characteristics of processing high-moisture content to a solid coal-like product. Five biomass feedstocks – wheat straw, pine, grape pomace, animal manure, and algae – were analyzed. The characteristics, as well as mass and energy yields of hydrochars and biochars from these feedstocks, were compared. Process simulation models were developed for both processes for each feedstock and techno-economic assessments conducted. The results indicate that hydrochars have superior characteristics, more coal-like properties, lower yields, and a higher cost of production (COP) than biochars for all cases except the pathways using manure as feedstock, where hydrochar COP is lower. The lowest production costs (without carbon credit) can be achieved through dry and wet torrefaction of grape pomace at 2.29 $/GJ and 4.14 $/GJ, respectively. Sensitivity and uncertainty analyses were also conducted for all pathways to understand the effects on production cost of varying different technical and economic factors. The results of this study will provide valuable insights into coal alternative products, especially in jurisdictions (like Alberta, Canada) planning to phase out coal plants. • Biocoal production via wet (WT) and dry (DT) torrefaction processes is investigated. • Five feedstocks (wheat straw, pine, grape pomace, manure, and algae) are studied. • Mass and energy yields and production costs (w and w/o carbon credit) are assessed. • Cost of biocoal production (COP) is competitive with coal price in some pathways. • Grape pomace has the lowest COP at 2.30 $/GJ and 4.15 $/GJ for DT and WT processes, respectively. [ABSTRACT FROM AUTHOR]

Bio-oil, produced through fast pyrolysis, can act as an intermediate, which can be further upgraded to biofuels. Fast pyrolysis is done in either a centralized or a decentralized (mobile pyrolysis system [MPS]) system. In a centralized system, biomass is transported to a plant to produce bio-oil, which is upgraded in the same unit, while in a decentralized system, the mobile plant is moved to the forest to produce bio-oil, which is transported to an upgrading facility. The objective of this study is to develop supply chain models and conduct a techno-economic assessment of bio-oil production in these two systems using the developed models. For both systems, the bio-oil plant capacity is considered to be 2000 dry t d−1. Because the capacity of an MPS ranges from 10 to 100 dry t d−1, several mobile pyrolysis units are required to achieve the target bio-oil produced in the base case capacity. In this study, models were developed for each supply chain network allocation scenario/configuration for MPS site location (the radial scenario and the truncated scenario) and four relocation time scenarios were assumed (yearly, semi-annually, quarterly, and monthly). Then, bio-oil production costs were evaluated and compared those with a centralized plant. For a 2000 dry t d−1 biomass plant, bio-oil production costs are 0.241$ L−1, 0.349 $ L−1, and 0.407 $ L−1 for the centralized plant, the MPS truncated scenario (100 dry t d−1 MPS unit, yearly relocation), and the MPS radial scenario (100 dry t d−1 MPS unit, yearly relocation), respectively. • Centralized and mobile pyrolysis systems (MPS) were investigated to produce bio-oil. • The capacity of an MPS unit ranged from 10 to 100 dry t d−1. • For an MPS, two allocation scenarios were considered: radial and truncated. • Bio-oil production costs for the two systems were assessed and compared. • The base case plant capacity was varied for both systems. [ABSTRACT FROM AUTHOR]