The electrification of industrial heat is a promising pathway for decarbonization, yet challenges persist in balancing capital costs, operating costs, and emissions reduction. While previous studies have assessed electrification through heat integration and graphical methods, these approaches do not inherently determine the optimal hybrid technology configuration. This study introduces an optimization-based framework that systematically evaluates the cost-optimal allocation of electrified and conventional heating technologies. Formulated as a Mixed-Integer Linear Programming (MILP) model and implemented in Gurobi, the framework minimizes Total Annualized Cost (TAC) while satisfying heat demand, technology constraints, and emissions targets. Applied to an industrial case study, the model compares three scenarios: a fully conventional system relying on steam boilers and fired heaters, a fully electrified system utilizing high-temperature heat pumps, electrode boilers, and electric heater... [more]

This work explores Aotearoa-New Zealand’s potential to fully electrify and source industrial process heat demands from renewable energy for 286 industrial sites while exploring the feasibility of green methanol production using excess electricity. Most energy models rely on spatially aggregated supply and demand, which limits the accurate representation of energy value chains. To address this limitation, the model incorporates industrial sites with varied temperature profiles, enabling the use of diverse heating technologies such as heat pumps, electrode boilers, bubbling fluidised bed reactors and biomass boilers. The proposed Mixed-Integer Linear Programming energy model uses the Accelerated Branch-and-Bound (ABB) algorithm, which is implemented within the P-graph framework to optimise the system. The model considers different energy transportation modes, including road transport for biomass and grid infrastructure for electricity. The multi-period design determines optimal heating t... [more]

In the last decades, the growing awareness of climate change and the high political sensitivity of critical resources such as energy have emphasized a need for local, renewable and optimized energy mixes at various scales. Several studies have therefore aimed to optimize renewable energy technologies and plant locations to develop more renewable and efficient Energy Mixes. Following this trend, this paper applies and compares Goal Programming, Branch-and-Cut and NSGA-II to a multi-objective combinatorial optimization problem focused on the energy mix of Oise, France. Results show more optimality for Goal Programming and Branch-and-Cut, accompanied by a high sensitivity to constraints, while NSGA-II provides more technological diversity in the computed solutions.

The unit commitment problem determines the optimal strategy to meet the electricity demand at minimum cost by committing power generation units at each point of time. Solving the unit commitment problem gives rise to a challenging optimization problem due to its combinatorial complexity and potentially long solution time requirements. Our proposed solution approach utilizes a decomposition method in conjunction with alternative models from the EGRET library. Results of this decomposition approach tested against four benchmarking systems show that significant computational speed ups are achieved.

Green hydrogen will play a key role in the decarbonization of the steel sector via the direct reduction path [1]. To meet the demand side, both a highly efficient numbering-up based scaling strategy for water electrolysis is needed as well as flexible operation strategies that follow the fluctuating electricity load. This paper presents a modularization approach for electrolysis systems that addresses both aspects by combining different electrolysis technologies into one heterogeneous electrolysis system. We present a modular design of such a heterogeneous electrolysis system that can be scaled for large-scale applications. The impact of different degrees of technological and production capacity-related heterogeneity is investigated using system co-simulation to find an optimal solution for the goal-conflict, that the direct reduction of iron for green steel production requires a constant stream of hydrogen while the renewable electricity profile is fluctuating. For this use-case the d... [more]

Real-time carbon accounting is crucial for advancing policies that effectively meet sustainability objectives. This work introduces a carbon tracking tool specifically designed for the European electricity grid. The tool collects hourly data on electricity consumption and generation, cross-border power exchanges, and weather information to assess the real-time environmental effects of electricity use, employing locally-specific emission factors for the generation sources. It utilizes weather data from various stations across Europe to produce week-ahead forecasts of carbon intensity in the grid. Predictions are created using a random forest regressor, integrated within the optimal controller of an operational industrial batch process. This prediction-based optimizer seeks to reduce total emissions tied to the process schedule's electricity consumption by implementing a rolling horizon strategy. By leveraging enhanced energy flexibility, the controller provides significant opportunities... [more]

This document contains digital supplementary material (detailed model description, parameters for different case studies and figure of exemplary waste heat supply and heat demand) related to the article "A Data-Driven Conceptual Approach to Heat Pump Sizing in Chemical Processes with Fluctuating Heat Supply and Demand" which is submitted to the peer reviewed conference proceeding of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).

Achieving sustainability in the energy sector re-quires an economically viable path with a balanced tran-sition that does not aggravate environmental and socio-logical problems associated with current fossil-based power production. Increasing the grid penetration of intermittent renewables to realize a sustainable energy future without consideration of the balanced transition may result in devastating economic and societal impacts [1]. As we press for the minimization of renewable power curtailment, current fossil-based technology struggles to meet demand under extreme transient and part-load conditions. This results in dramatic reduction of efficiency and a corresponding increase in emissions of not only carbon, but far more devastating pollutants... (ABSTRACT ABBREVIATED)

The United States’ Inflation Reduction Act (IRA) of 2022 has established incentives to facilitate the energy transition. While these policies provide economic incen-tives that encourage investment and may reduce financial risk for the private sector on the supply side, transitioning to a lower carbon or net-zero economy by 2050 presents several challenges. These include designing flexible production systems that can interact with inter-mittent renewable energy resources, ensure process safety, redesigning existing energy infrastructure to support new energy carriers like hydrogen or ammonia, and making long-term investment decisions in an uncertain and evolving market... (ABSTRACT ABBREVIATED)

There is a need to drastically reduce greenhouse gas emissions. While significant progress has been made in electrifying transport, heavy duty transportation and aviation are not likely to be capable of electrification in the near term, spurring significant research into biofuels. When coupled with carbon capture and storage, biofuels can achieve net-negative greenhouse gas emissions via many different conversion technologies such as fermentation, pyrolysis, or gasification to produce ethanol, gasoline, diesel, or jet fuel. However, each pathway has a different efficiency, capital and operating costs, and potential for carbon capture, making the optimal pathway dependent on policy and spatial factors. We use the Integrated Markal-EFOM System model applied to the USA, adding a rich suite of biofuel and carbon capture technologies, region-specific CO2 transportation and injection costs, and government incentives from the Inflation Reduction Act. We find that under current government ince... [more]

To mitigate the effects of catastrophic failure while maintaining resource and production efficiencies, energy systems need to be designed for resilience and sustainability. Conventional approaches such as redundancies through backup processes or inventory stockpiles demand high capital investment and resource allocation. In addition, responding to unexpected “black swan” events requires that systems have the agility to transform and adapt rapidly. To develop targeted solutions that protect the system efficiently, the supply chain network needs to be considered as an integrated multi-scale system incorporating every component from individual process units all the way to the whole network. This approach can be readily integrated with analogous multiscale approaches for sustainability, safety, and intensification. In this work, we bring together classical supply chain resilience with process systems engineering to leverage the multi-scale nature of energy systems for developing resilienc... [more]

The placement of wind turbines is a crucial design element in wind farms, given the energy losses resulting from the wake effect. Despite numerous studies addressing the Wind Farm Layout Optimization (WFLO) problem, considering multiple directions to determine wind turbine spacing and layout remains limited. However, relying solely on one predominant direction may lead to overestimating energy production, and loss of energy generation. This work introduces a novel mathematical programming optimization framework to solve the WFLO problem, emphasizing the wind energy's nonlinear characteristics and wake effect losses. Comparisons with traditional layout approaches demonstrate the importance of optimizing wind farm layouts during the design phase. By providing valuable insights into the renewable energy sector, this research aims to guide future wind farm projects towards layouts that balance economic considerations with maximizing energy production.

The transition to net-zero greenhouse gas emissions requires a rapid redesign of energy systems. However, the redesign may shift environmental impacts to other categories than climate change. To assess the sustainability of the resulting impacts, the planetary boundaries framework provides absolute limits for environmental sustainability. This study uses the planetary boundaries framework to assess net-zero sector-coupled energy system designs for absolute environmental sustainability. Considering Germany as a case study, we extend the common focus on climate change in sustainable energy system design to seven additional Earth-system processes crucial for maintaining conditions favorable to human well-being. Our assessment reveals that transitioning to net-zero greenhouse gas emissions reduces many environmental impacts but is not equivalent to sustainability, as all net-zero designs transgress at least one planetary boundary. However, the environmental impacts vary substantially betwe... [more]

We study the impact of switching from combustion heating to electric heating in processes comprising high temperature reaction/separation sequences, where the heat supporting the reaction(s) is substantially provided by combusting a reaction byproduct (fuel gas). A canonical process structure is de?ned. It is shown that the conventional combustion- based process presents signi?cant interactions. An asymptotic analysis is utilized to investigate and compare the dynamic responses of the conventional and electric process configurations. It is demonstrated that the dynamic behavior of the two processes exhibits two timescales, with the faster corresponding to the evolution of the temperatures of the units with high heat duty, and the slow time scale capturing the variables involved in the material balance. A simpli?ed ethylene cracking process example is used to demonstrate these findings.

An important measure to achieve global reduction in CO2 emissions is CO2 capture, transport, and storage. The deployment of CO2 capture requires the development of a shared CO2 transport infrastructure, where CO2 can be transported with different transport modes. Furthermore, the cost of CO2 transport can be subject to significant economies of scale effects with respect to the amount of CO2 transported, also mentioned as clustering effects. Therefore, optimizing the shared infrastructure of multiple CO2 sources can lead to significant reductions in infrastructure costs. This paper presents a novel formulation of the clustered CO2 transport network. The Markov Decision Process formulation defined here allows for more detailed modeling of non-linear, discrete transport costs and increased geographical resolution. The clustering effects are modeled through cooperative multi-agent interactions. A multi-agent, reinforcement learning-based algorithm is proposed to optimize the shared transpo... [more]

With growing concern over the effects of green-house gas emissions, there has been an increase in emission-reducing policies by governments around the world, with over 70 countries having set net-zero emission goals by 2050-2060. These are ambitious goals that will require large investments into the expansion of renewable and low-carbon technologies. The decisions about which technologies should be invested in can be difficult to make since they are based on information about the future, which is uncertain. When considering emerging technologies, a source of uncertainty to consider is how the costs will develop over time. Learning curves are used to model the decrease in cost as the total installed capacity of a technology increases. However, the extent to which the cost decreases is uncertain. To address the uncertainty present in multiple aspects of the energy sector, multistage stochastic programming is employed considering both exogenous and endogenous uncertainties. It is observed... [more]

Increasing wind and solar electricity generation in power systems increases temporal variability in electricity prices which incentivizes the development of flexible processes for electricity generation and electricity-based fuels/chemicals production. Here, we develop a computational framework for the integrated design and optimization of multi-product processes interacting with the grid under time-varying electricity prices. Our analysis focuses on the case study of nuclear-based hydrogen (H2) and electricity generation, involving nuclear power plants (NPP) producing high temperature heat and electricity coupled with a high temperature steam electrolyzers (HTSE) for H2 production. The ability to co-produce H2 along with nuclear is widely seen as critical to improving the economics of nuclear energy technologies. To that end, our model focuses on evaluating the least-cost design and operations of the NPP-HTSE system while accounting for: a) power consumption variation with current den... [more]

The decarbonization of the society has a very high effect on the power grids as especially the energy generation will be almost completely shifted to CO2-neutral sources such as wind and solar. This implies significant design changes to the power grids and power systems, which lie between the electricity producers and consumers. In this paper, we discuss both the generation and consumer side, including the grid changes and required data exchange to support the transition.

Developing methods for rapid, large-scale deployment of carbon capture systems is critical for meeting climate change goals. Optimization-based decisions can be employed at the design and manufacturing phases to minimize the costs of deployment and operation. Manufacturing standardization results in significant cost savings due to economies of numbers. Building on previous work, we present a process family design approach to design a set of carbon capture systems while explicitly including economies of numbers savings within the formulation. Our formulation optimizes both the number and characteristics of the common components in the platform and simultaneously designs the resulting set of carbon capture systems. Savings from economies of numbers are explicitly included in the formulation to determine the number of components in the platform. We show and discuss the savings we gain from economies of numbers.

This review focuses on analysing the strategy and aspirations of the European Union within the hydrogen sector. This aim is achieved through the examination of the European Parliament’s hydrogen strategy, allowing for a study of actions and projects in hydrogen technologies. The Parliament’s hydrogen strategy is the document that provides the guideline of how the EU intends to function in the hydrogen sector and manages to cover a wide range of topics, all of them significant to represent the entirety of the hydrogen sector. It touches on subjects such as hydrogen demand, infrastructure, research, and standards, among others. The review discusses also the aspect that the EU intends to be a leader in the hydrogen sector, including the large-scale industrialization of key elements such as electrolysers, and this purpose is corroborated by the large number of associations, strategies, plans, and projects that are being established and developed by the European Union. The most important co... [more]

Lightweight design is a common approach to reduce energy demand in the use stage of vehicles. The production of lightweight materials is usually associated with an increase in energy demand, so the environmental impacts of lightweight structures need to be assessed holistically using a life cycle assessment. To estimate the life cycle environmental impacts of a product in its developmental stage, for example, by life cycle engineering, future changes in relevant influencing factors must be considered. Prospective life cycle assessment provides methods for integrating future scenarios into life cycle assessment studies. However, approaches for integrating prospective life cycle assessment into product development are limited. The objective of this work is to provide the methodological foundation for integrating future scenarios of relevant influencing factors in the development of lightweight structures. The applicability of the novel methodology is demonstrated by a case study of a str... [more]

High altitude airships possess tremendous potential for long-endurance spot hovering platforms for both commercial and strategic applications. The energy system, which is mainly made up of solar array and regenerative fuel cell, is the key component of a high altitude airship. The thermal effect is a major factor that affects the performance of the energy system of long endurance stratospheric vehicles. In this paper, a conceptual design method focusing on the thermal and power characteristics of an energy system for stratospheric airships is proposed. The effect of thermal behavior of solar array on the energy system is analyzed. An optimized case is obtained on the consideration of power supply, thermal behaviors of helium and solar array. Results show that the maximum temperature difference of the solar array may be reduced by about 20 K and the mass of payload can be improved by up to 5%.

Currently, international business and society are on the eve of large-scale changes. The study aims to develop a methodological approach to assess the energy flexibility of multinational corporations in the context of the structural transformation management of renewable energy production. The methodology of this study is based on a comprehensive approach, which includes the methodology of the United States Agency for International Development (USAID), diagnostics of the level of development and energy flexibility of multinational corporations, regression analysis and scenario modeling. In particular, scenario analysis of renewable energy development in countries of the Commonwealth of Independent States (CIS) and economic analysis of projects for the development of corporate renewable energy industry were carried out. The results showed that the Russian renewable energy business is flexible enough for changes; however, at the same time, changes are needed in the national legislation,... [more]

Public attention to climate change challenges our locked-in fossil fuel-dependent energy sector. Natural gas is replacing other fossil fuels in our energy mix. One way to reduce the greenhouse gas (GHG) impact of fossil natural gas is to replace it with renewable natural gas (RNG). The benefits of utilizing RNG are that it has no climate change impact when combusted and utilized in the same applications as fossil natural gas. RNG can be injected into the gas grid, used as a transportation fuel, or used for heating and electricity generation. Less common applications include utilizing RNG to produce chemicals, such as methanol, dimethyl ether, and ammonia. The GHG impact should be quantified before committing to RNG. This study quantifies the potential production of biogas (i.e., the precursor to RNG) and RNG from agricultural and waste sources in New York State (NYS). It is unique because it is the first study to provide this analysis. The results showed that only about 10% of the stat... [more]

As for research on sector-coupled energy systems, few studies comprehensively deal with energy carriers and energy demand sectors. Moreover, few studies have analyzed energy conversion functions such as Power-to-Gas, Power-to-Heat, and Vehicle-to-Grid on the energy system performance. This study clarifies the required renewable resources and costs in the sector-coupled energy system and cost-optimal installed capacity and operation. We formulated an optimization model considering sector coupling and conducted a case study applying the model in the Tohoku region. As a result, due to sector coupling, the total primary energy supply (TPES) is expected to decrease, and system costs are expected to increase from 1.8 to 2.4 times the current level. System costs were minimized when maximizing the use of V2G by electric vehicles and district heating systems (DHS). From the hourly analysis, it becomes clear that the peak cut effect by Power-to-Heat and the peak shift effect by Vehicle-to-Grid r... [more]