• Energy Research

This study investigates the technical and economic feasibility of replacing throttling valves with smale-scale, oil-free turbomachinery in industrial steam networks. This is done from the perspective of the turbomachine, which has to be integrated into a new or existing process. The considered machines have a power range of P=[0.5,…,250 kW] and have been designed using real industrial data from existing processes. Design guidelines are developed, which take into account the thermodynamic process as well as engineering aspects of such a turbomachine. The results suggest that steam conditioning prior to heat exchange could be completed by small expanders to produce mechanical work, reducing exergy destruction and improving site-wide energy efficiency compared to throttling valves. Cost estimates for such machines are presented, which serve as a basis for case-specific investment calculations. The resulting payback times of less than 18 months highlight the economic potential such solutions.

Industries consume large quantities of energy and water in their processes which are often considered to be peripheral to the process operation. Energy is used to heat or cool water for process use; additionally, water is frequently used in production support or utility networks as steam or cooling water. This enunciates the interconnectedness of water and energy and illustrates the necessity of their simultaneous treatment to improve energy and resource efficiency in industrial processes. Since the seminal work of Savulescu and Smith in 1998 introducing a graphical approach, many authors have contributed to this field by proposing graphically- or optimization-based methodologies. The latter encourages development of mathematical superstructures encompassing all possible interconnections. While a large body of research has focused on improving the superstructure development, solution strategies to tackle such optimization problems have also received significant attention. The goal of the current article is to study the proposed methodologies with special focus on mathematical approaches, their key features and solution strategies. Following the convention of Jeżowski, solution strategies are categorized into: decomposition, sequential, simultaneous, meta-heuristics and a more novel strategy of relaxation/transformation. A detailed, feature-based review of all the main contributions has also been provided in two tables. Several gaps have been highlighted as future research directions.

Abstract Due to the global increase in energy consumption, greenhouse gas emissions, and the depletion of fossil energy resources, the research presented here is focused on finding economically and environmentally competitive renewable energy resources. Fuel production from biomass is an attractive solution in this regard. Competing interests between food and energy have yielded increased interest in lignocellulosic biomass (LGB) as a feedstock. Processes such as biodiesel production from palm oil generate large volumes of LGB residues. Valorization of these residues through biorefineries may bring economic and environmental benefits through substitution of fossil fuels and such options must be studied in a systematic manner. The goal of this research is to propose a methodology for economic and environmental analysis of such biorefineries. A case study of a palm-based biorefinery in Brazil is used to illustrate this. Results indicate that multi-product processes can yield significant cost and environmental benefits.

Abstract Conservation and demand management of electricity is actively being pursued within the province of Ontario, Canada in an attempt to avoid new facility construction, manage costs, reduce emissions and also relieve stress on the electricity grid. The research presented here examines the consumption patterns of residential householders when provided with near-real-time, disaggregated electricity consumption data. Correlation coefficients are calculated between grouped appliance consumption and overall load-shifting or conservation patterns. Results show that householders who shift loads to off-peak do so by modifying consumption patterns of active loads in specific consumption categories. Conservation behavior is found in two of 18 households and is correlated to the consumption pattern of air conditioning units, major and discretionary loads. Policy focusing on conservation and demand management should therefore be specifically developed to stimulate the desired response from residential customers.

Production data in process industry are proprietary to a company since they are key to the process design and technology expertise. However, data confidentiality restrains industry from sharing results and advancing developments in and across process sectors. Using virtual profiles that simulate the typical operating modes of a given process industry offers an elegant solution for a company to share information with the outside world. This paper proposes a generic methodology to create sector blueprints and applies it to the chemicals industry. It details the profile of a typical chemical site based on essential units and realistic data gathered from existing refineries and chemical plants.

Abstract Excessive electricity consumption during peak demand periods has been shown to be expensive for utility companies and can affect the stability of the electricity grid. Shifting peak electricity consumption to off-peak periods has attracted the interest of governments, utility companies, equipment manufacturers and residents. Individual, hourly, household data from Ontario, Canada are used to explore the potential for households to install electricity storage systems by manipulating two financial policy triggers. Results show that households with higher daily and on-peak consumption realize net benefits at lower deviations from the current pricing regimes than do those with lower consumption. Benefits for households can be realized by manipulating either of the policy triggers considered, although the feasibility of these policy decisions is not explored. Repurposed Li-ion batteries require complete subsidy on re-purposing and installation of the system with a $29 kWh capacity −1 subsidy or a differential of 19.5 ¢ kWh −1 between on- and off-peak commodity rates for 10% of households to achieve net benefits. Systems with new ZnMnO 2 batteries require a $44 kWh capacity −1 subsidy in addition to a complete installation subsidy or a differential of 16.5 ¢ kWh −1 between on- and off-peak commodity prices to achieve the same proportion of households with net benefits.

Efficient consumption of energy and material resources, including water, is the primary focus for process industries to reduce their environmental impact. The Conference of Parties in Paris (COP21) highlighted the prominent role of industrial energy efficiency in combating climate change by reducing greenhouse gas emissions. Consumption of energy and material resources, especially water, are strongly interconnected and, therefore, must be treated simultaneously using a holistic approach to identify optimal solutions for efficient processing. Such approaches must consider energy and water recovery within a comprehensive process integration framework which includes options such as organic Rankine cycles for electricity generation from low–medium-temperature heat. This work addresses the importance of holistic approaches by proposing a methodology for simultaneous consideration of heat, mass, and power in industrial processes. The methodology is applied to a kraft pulp mill. In doing so, freshwater consumption is reduced by more than 60%, while net power output is increased by a factor of up to six (from 3.2 MW to between 10–26 MW). The results show that interactions among these elements are complex and therefore underline the necessity of such comprehensive methods to explore their optimal integration with industrial processes. The potential applications of this work are vast, extending from total site resource integration to addressing synergies in the context of industrial symbiosis.

The industrial sector has a large presence in world energy consumption and CO2 emissions, which has made it one of the focal points for energy and resource efficiency studies. However, large investments are required to retrofit existing industrial plants, which remains the largest barrier to implementing energy saving solutions. Process integration methods can be used to identify the best investments to improve the efficiency of plants, yet their timing remains to be answered using an optimisation approach. Even more critically, such decisions must also account for future investments to avoid stranded or regretted investments. This paper presents a method incorporating investment planning over long time horizons in the framework of process integration. The time horizon is included by formulating the problem using multiple investment periods. Investment planning is conducted using a superstructure approach, which permits both commissioning and decommissioning of units in the beginning of each period. The method is applied to a large case study, with an industrial cluster neighbouring an urban centre to also explore options of heat integration between industries and cities. Compared to the business-as-usual operation, optimal investment planning improves the operating cost of the system by 27% without budget constraints and 16–26% with constraints on budget and investment periods, which is reflected as an increase in net present value and a decrease in CO2 emissions. In all cases, the operating cost benefits pay off the investment in less than two years. The present work is efficient in finding energy saving solutions based on the interest of industries. This method adds additional perspectives in the decision-making process and is adaptable to various time horizons, budgets and economic constraints.