• Energy Research

The large potential for waste resource and heat recovery in industry has been motivating research toward increasing efficiency. Process integration methods have proven to be effective tools in improving industrial sites while decreasing their resource and energy consumption; however, location aspects and their impact are generally overlooked. This paper presents a method based on process integration, which considers the location of plants. The impact of the locations is included within the mixed integer linear programming framework in the form of heat losses, temperature and pressure drop, and piping cost. The objective function is selected as minimisation of the total cost of the system excluding piping cost and ϵ -constraints are applied on the piping cost to systematically generate multiple solutions. The method is applied to a case study with industrial plants from different sectors. First, the interaction between two plants and their utility integration are illustrated, depending on the piping cost limit which results in the heat pump and boiler on one site being gradually replaced by excess heat recovered from the other plant. Then, the optimisation of the whole system is carried out, as a large-scale application. At low piping cost allowances, heat is shared through high pressure steam in above-ground pipes, while at higher piping cost limits the system switches toward lower pressure steam sharing in underground pipes. Compared to the business-as-usual operation of the sites, the optimal solution obtained with the proposed method leads to 20% reduction in the overall cost of the system, including the piping cost. Further reduction in the cost is possible using a state of the art method but the technical and economic feasibility is not guaranteed. Thus, the present work provides a tool to find optimal industrial symbiosis solutions under different investment limits on the infrastructure between plants.

Life cycle impact assessment indicators are integrated for studying the process integration of renewable resources and CO2 capture and storage (CCS) in power plants. Besides the expected reduction in global warming potential (GWP), CCS induces energy and cost penalties. This paper presents a systematic multi-objective optimisation framework for the optimal design of power plants with CO2 capture considering environomic criteria to systematically assess the trade-off between environmental impacts, efficiency and costs. Life cycle assessment is combined with flowsheeting, energy integration, economic evaluation and multi-objective optimisation techniques. Post- and pre-combustion CO2 capture options for electricity generation processes, using fossil and renewable resources, are assessed. Multi-objective optimisations are performed for various objectives to reveal the influence on the decision making. The calculated CO2 emissions, allow to assess the impact of the CO2 tax, considering not only the on-site emissions but taking into account the overall life cycle of the fuel supply, electricity generation and CO2 capture. The results show that the environomic optimal process design and competitiveness of CO2 capture highly depends on the considered environmental impact and on the introduction of a carbon tax.

In the face of escalating climate concerns and the push for sustainable development, the global shift towards renewable and decentralized energy systems presents new challenges and opportunities. This study investigates integrating decentralized energy production, particularly photovoltaic (PV) systems, into national energy planning, aiming to optimize energy strategies that balance local production and consumption with national objectives. By analyzing the Swiss energy model, the research employs the EnergyScope and REHO models to assess the strategic implications of decentralized versus centralized energy systems. Results show that a decentralized approach can significantly reduce PV installation needs to 35 GW, about 23% of potential capacity, and decrease annual system costs by 10% to CHF 1230 per capita. This strategy emphasizes local consumption, minimizes grid reinforcement demands, and leverages economic advantages while addressing overproduction challenges through effective energy storage and grid management. Conclusions underline the strategic value of combining centralized and decentralized methods for resilient and sustainable energy planning. The study contributes to the discourse on energy policy and infrastructure planning, advocating for a hybrid model that accommodates both local conditions and broader energy objectives, urging further research into climate impacts and technology integration for a comprehensive energy future.

AbstractA systematic comparison and optimization of thermo-chemical hydrogen production processes with CO2 capture is performed. The process options include the resource type, the syngas production method and the hydrogen purification technology, including CO2 separation by ab- or adsorption or membrane processes. With regard to climate change mitigation, the removed CO2 can be compressed for storage. To analyze the competitiveness of different CO2 capture options and H2 process alternatives a consistent multi-objective optimization methodology combining energy-flow models with process integration techniques and economic and environmental evaluation is applied. The potential of efficient decarbonization in fossil and renewable H2 processes is highlighted.

The design and operations of energy systems are key issues for matching energy supply and consumption. Several optimization methods based on the mixed integer linear programming (MILP) have been developed for this purpose. However, due to uncertainty of some parameters like market conditions and resource availability, analyzing only one optimal solution with mono objective function is not sufficient for sizing the energy system. In this study, a multi-period energy system optimization (ESO) model with a mono objective function is first explained. The model is then developed in a multi-objective optimization perspective to systematically generate a good set of solutions by using integer cut constraints (ICC) algorithm and e constraint. These two methods are discussed and compared. In the next step, the ESO model is reformulated as a multi-objective optimization model with an evolutionary algorithm (EMOO). In this step the model is decomposed into master and slave optimization. Finally developed models are demonstrated by means of a case study comprising six types of conversion technologies, namely, a heat pump, boiler, photovoltaics, as well as a gas turbine, fuel cell and gas engine. Results show that, EMOO is particularly suited for multi-objective optimizations, working with a population of potential solutions, each presenting a different trade-off between objectives. However, MILP with ICC and e constraint is more suited for generating a small set of ordered solutions with shorter resolution time.

Abstract The design criteria for modern sustainable development of vehicle powertrain are the high energy efficiency of the conversion system, the competitive cost and the lowest possible environmental impacts. In this article a multi-objective optimization methodology is applied on hybrid electric vehicles study in order to define the optimal powertrain configurations of the vehicle, estimate the cost of the powertrain equipment and show the environmental impact of the technical choices on the lifecycle perspective of the vehicle. The study illustrates optimal design solutions for low fuel consumption vehicles – between 2 L/100 km and 3 L/100 km. For that a simulation model of a hybrid electric vehicle is made. This model is coupled with a cost model for the vehicle. The techno–economic optimizations are performed for two case studies, illustrating the possibilities of the optimization superstructure. Firstly the life cycle inventory is written as a function of the parameters of the techno–economic model. In this way, the obtained environmental indicators from the life cycle assessment are calculated as a function of the decision variables for the vehicle design. In the second example the parameters of the energy distribution function are included as decision variables in the techno–economic optimization and are simultaneously optimized.

A growing number of technologies are being developed in order to produce different high added value products, such as phytochemicals, ethanol and other chemicals from biomass, representing an important trend that needs to be evaluated. The use of pressurized-fluid technologies to obtain phytochemicals from certain biomasses has shown encouraging results in terms of selectivity, enabling its use prior bioenergy generation since generally only a small part of the solid material is extracted. The phytochemical compound which is most financially interesting to extract from the Brazilian Ginseng (Pfaffia glomerata) roots is ecdysterone (ß-ecdysone), an ecdysteroid. Ecdysteroids are a class of natural steroids acting as hormones and ß-ecdysone is the most important steroid employed in cosmetic formulations. It is also used in other industries such as the food and pharmaceutical industry. Due to its health properties, large amounts of Pfaffia glomerata roots are being exported from Brazil to countries that use phytochemical therapies widely. This work is part of a project that aims to present a solution to perform phytochemicals recovery step in Brazil envisioning decentralized local-scale production. In this study, first the influence of the extraction temperature (353–413 K) and static extraction time (5–15 min) using pressurized ethyl acetate as extracting solvent on the ß-ecdysone recovery was experimentally evaluated and compared with literature results employing other pressurized fluids. Afterwards, an economical analysis was done for comparison using ASPEN PLUS software and OSMOSE platform. It was observed that the relationship of the ß-ecdysone recovery, extraction temperature and static extraction time was linear. An increase in temperature and static time resulted in enhancement of the ß-ecdysone recovery from the biomass. On the other hand, the increase of the extraction temperature beyond 373 K possibly might enhance the degradation of the ß-ecdysone extracted decreasing its relative amount in the extract. Since for the economical analysis performed the former response variable (ß-ecdysone recovery) is most important than the latter, it was calculated the net present value of this process considering high extraction temperatures. Considering an installation time of two years, a lifetime of 25 years and an interest rate of 15 % the obtained net present value for the different pressurized extracting solvents were in the following order: ethyl acetate > ethanol > CO2-ethanol mixture. The results demonstrate that the inclusion of a pressurized fluid-based process using ethyl acetate or ethanol for ß-ecdysone recovery prior further bioenergy production is very promising.