• Energy Research

Abstract The European Union (EU) has the world's most extensive regional power trade, making it essential for the EU environmental energy policies. Understanding the nexus amongst water, power and CO2 emissions is essential for sustainable water and energy resource management. Although a number of related studies on the nexus have been conducted, integrating virtual water and CO2 emission footprints for the power sector requires further attention. The current study analyses the virtual water and CO2 emissions embodied in the power supply, demand and regional trade. A network model is developed to track the virtual water and CO2 emissions of the inter-regional power trade for the case of EU-27 countries in 2017. The total virtual CO2 emissions and the embodied virtual water in the EU inter-regional power trade are estimated as 7.0 × 104 t CO2 and 5.6 × 108 m3, with a hydropower contribution of 37.8%. The largest virtual water and CO2 emissions exporters are identified by France (8.8 × 107 m3) and Germany (2 × 104 t), whilst the largest virtual CO2 importer is Austria (1 × 104 t). The identified synergy of climate mitigation and water scarcity provides a benchmark for policymakers to develop strategies for sustainable power development considering the virtual footprint in trade flow simultaneously.

This paper deals with analysis of energy consumption of Ukrainian bromine plant. Process integration allows reducing the energy consumption on 1.5 MW by heat recovery. It is achieved by improvement of recuperative heat exchangers network. Additionally heat recovery may be increased by multistage evaporation of sodium bromide and ferrous chloride. Increase the heat recovery leads utility reduction. This is not only heating and cooling duty but also power pumping and pipe heat losses. The investment for retrofit project is about 757 100 € and payback period about 2 years.

Abstract A method for regional energy targeting and supply chains synthesis is presented. A demand-driven approach is applied to assess the feasible ways for transferring energy from renewable sources to customers in a given region. The studied region is partitioned into a number of clusters by using the Regional Energy Clustering (REC) algorithm. The REC targets aim at minimising the system carbon footprint (CFP). Energy supply chain synthesis is performed next within each cluster by using the P-graph framework. The synthesis algorithm generates a maximal structure of all feasible options and optimal structure is obtained by minimising the energy cost and carbon footprint.

Abstract Total Site (TS) analysis for incorporating short-term or daily energy variation has been introduced in the previous studies as an extension of the Time Slice Model for the Heat Integration of batch processes. However, the energy supply and demand fluctuation could also be affected by changing customer demands due to seasonal climate variations, economic downturn, maintenance, plant turn-around, plant operability issues and raw material availability. This paper extended the cascade energy targeting methodology for TSHI incorporating long- and short-term heat energy supply and demand variation problem. The methodology aims to estimate the energy requirements of the TS system considering seasonal energy storage system as a feasibility study for energy efficiency project. A newly extended algebraic tool, known as Seasonal Total Site Heat Storage Cascade (Seasonal TS-HSC), is introduced in the methodology for modelling the energy flow between process units and storage facilities. The general tool could be used for different storage systems. This proposed tool includes the estimation of energy losses through self-discharge, charge and discharge process based on the energy storage system performance. The methodology is illustrated by a case study, which integrates batch processes, community buildings and space heating system. Implementation of the developed methodology on the case study resulted in 93.4% (low-pressure steam - LPS) and 38.2% (hot water - HW) heating requirement reduction via seasonal energy storage system application at two utility levels. The result shows the energy requirement reduction, which contributes to profitability margin improvement, greenhouse gas emission reduction potential and regional sustainability enhancement, through seasonal energy storage system in the industrial energy system.

Large amounts of thermal energy are transferred between fluids for heating or cooling in industry as well as in the residential and service sectors. Typical examples are crude oil preheating, ethylene plants, pulp and paper plants, breweries, plants with exothermic and endothermic reactions, space heating, and cooling or refrigeration of food and beverages. Heat exchangers frequently operate under varying conditions. Their appropriate use in flexible heat exchanger networks as well as maintenance/reliability related calculations requires adequate models for estimating their dynamic behaviour. Cell-based dynamic models are very often used to represent heat exchangers with varying arrangements. The current paper describes a direct method and a visualisation technique for determining the number of the modelling cells and their size.

A new view is presented on the concept of the combined cycle for power generation. Traditionally, the term “combined cycle” is associated with using a gas turbine in combination with steam turbines to better utilize the exergy potential of the burnt fuel. This concept can be broadened, however, to the utilization of any power-generating facility in combination with steam turbines, as long as this facility also provides a high-temperature waste heat. Such facilities are high temperature fuel cells. Fuel cells are especially advantageous for combined cycle applications since they feature a remarkably high efficiency—reaching an order of 45–50% and even close to 60%, compared to 30–35% for most gas turbines. The literature sources on combining fuel cells with gas and steam turbines clearly illustrate the potential to achieve high power and co-generation efficiencies. In the presented work, the extension to the concept of combined cycle is considered on the example of a molten carbonate fuel cell (MCFC) working under stationary conditions. An overview of the process for the MCFC is given, followed by the options for heat integration utilizing the waste heat for steam generation. The complete fuel cell combined cycle (FCCC) system is then analyzed to estimate the potential power cost levels that could be achieved. The results demonstrate that a properly designed FCCC system is capable of reaching significantly higher efficiency compared to the standalone fuel cell system. An important observation is that FCCC systems may result in economically competitive power production units, comparable with contemporary fossil power stations.

Abstract This paper presents a new concept, distance potential, which is the sum of the distances from the source points to the demand point being considered (for supply chains), or the sum of the distances from the demand (customer) being considered to other demands and the depot (for vehicle routing problems). We also investigate the applications of the new concept to the design of regional biomass supply chains and solving vehicle routing problems. In designing a supply chain, the values of the distance potentials are used to determine the precedence order: the demand point with the largest distance potential value will be satisfied first. While satisfying a demand point, the source point with the shortest distance to the demand will be used first. In solving a vehicle routing problem, the new concept is used to identify the customer which should be included in the first routing to be considered. Then, the network can be designed starting from the customer identified, and based on a few heuristic rules proposed in this paper. The results obtained in this work are comparable to or even better than that obtained in the literature. It is shown that the method proposed is simple and of high computational efficiency.

Fluctuating renewable energy supply presents a challenge for applying energy-saving methodologies such as Process Integration. Graphical targeting procedures based on the Time Slices (TSLs) have been proposed in previous works to handle the energy supply/demand variability in TSHI. The targeting procedures for TSHI with TSLs include the construction of Composite Curves, Grand Composite Curve and Total Site Profile for each time interval. Heat Integration analysis utilising a numerical algorithm typically offers higher precision and more rapid calculations as compared to the graphical approach. This paper introduces an algorithm to efficiently perform utility targeting for a large-scale TSHI system involving renewable energy and variable energy supply/demand to include TSL. The presented tool is an extension of the Total Site Problem Table Algorithm (TS-PTA), which has been previously used for processes with steady energy supply/demand. Due to its algorithmic nature, the technique presented enables the accurate and rapid determination of the stream origins, and can be embedded into larger algorithms. Optimised heat storage facilities are used to manage the variable energy supply and demand. The Total Site Heat Storage Cascade (TS-HSC) is the core of the algorithm. The new developed tool is incorporated with the heat losses for the thermo-chemical energy storage systems. The process start-up and continuous operations are considered in the novel methodology. The tool is featured to analyse the heat excess in specific TSLs that can be cascaded to the next TSL via energy storage system during start-up and operation. The proposed tool can be also used to estimate the required heat storage capacity.