Energy-intensive Plants Research Articles

Improving bioenergy recovery from municipal wastewater with a novel cloth-filter anaerobic membrane bioreactor

Anaerobic membrane bioreactors (AnMBR) have been used for treating high-strength industrial wastewater at full-scale and the potential to use them for mainstream municipal wastewater treatment presents an important opportunity to turn energy-intensive plants into net-energy producers. However, several limitations of the AnMBR technology have prevented their adoption in the municipal wastewater industry, namely, high membrane cleaning energy demand and low membrane flux. This study demonstrated a novel AnMBR configuration that uses a commercially available cloth filter technology to address the key limitations of cleaning energy and membrane flux. The cloth filter anaerobic membrane bioreactor (CFAnMBR) is comprised of an anaerobic fixed-film bioreactor coupled with a cloth filter membrane with nominal pore size of 5 µm. The pilot CFAnMBR was operated for 150 days through the winter at a municipal wastewater plant in central Illinois (minimum/average influent temperature 5/13°C). The CFAnMBR increased membrane flux by more than 2 orders of magnitude (3,649 ± 1,246 L per meter squared per hour) and reduced cleaning energy demand by 78%—92% (0.0085 kWh/m3) relative to previously reported AnMBR configurations. With the CFAnMBR, average chemical oxygen demand and total suspended solids removal were 66% and 91%, respectively, and were shown to be increased up to 88% and 96% by in-line coagulant dosing with ferric chloride. Average headspace methane yield was 154 mL CH4/g CODremoved by the end of the study period with influent temperatures of 11°C± 4°C. The CFAnMBR resolves major limitations of AnMBR technology by employing a commercially-available technology already used for other municipal wastewater treatment applications.

Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors

In recent years, environmental concerns about climate change and global warming have encouraged countries to increase investment in renewable energies. As the penetration of renewable power goes up, the intermittency of the power system increases. To counterbalance the power fluctuations, demand-side flexibility is a workable solution. This paper reviews the flexibility potentials of demand sectors, including residential, industrial, commercial, and agricultural, to facilitate the integration of renewables into power systems. In the residential sector, home energy management systems and heat pumps exhibit great flexibility potential. The former can unlock the flexibility of household devices, e.g., wet appliances and lighting systems. The latter integrates the joint heat–power flexibility of heating systems into power grids. In the industrial sector, heavy industries, e.g., cement manufacturing plants, metal smelting, and oil refinery plants, are surveyed. It is discussed how energy-intensive plants can provide flexibility for energy systems. In the commercial sector, supermarket refrigerators, hotels/restaurants, and commercial parking lots of electric vehicles are pointed out. Large-scale parking lots of electric vehicles can be considered as great electrical storage not only to provide flexibility for the upstream network but also to supply the local commercial sector, e.g., shopping stores. In the agricultural sector, irrigation pumps, on-farm solar sites, and variable-frequency-drive water pumps are shown as flexible demands. The flexibility potentials of livestock farms are also surveyed.

Thermodynamic loss analysis of a liquid-sorbent direct air carbon capture plant

Direct air capture of CO 2 is often presented as a promising technology to help mitigate climate change, although proposed processes are highly energy intensive. We analyze Carbon Engineering’s 1 Mt-CO 2 /year natural-gas-powered direct air capture (DAC) process, which requires 273.2 MW per plant, where we find that 252 MW are irreversibly lost, corresponding to a second-law efficiency of 7.8%. Our component-level analysis details the mechanisms by which these losses of thermodynamic work potential occur in the most energy-intensive plant segments. Here, we emphasize the effects of chemical exergy dissipation in the air contactor, where stored chemical exergy is released as low-grade heat into the environment. Other major losses occur in the calciner and its preheat cyclones due to the high temperature demanded by its internal chemical reaction, as well as in the water knockout system, CO 2 compression system, and power island. Finally, we illustrate the issues arising from the use of natural gas as a feedstock for heat and power, and suggest directions to pursue for further analysis and process improvements, which we consider imperative to make this DAC process a viable option for large-scale CO 2 removal toward IPCC targets. • Full thermodynamic evaluation of a natural-gas-fueled liquid-sorbent DAC plant • Total destroyed exergy of 252 MW for 273.2 MW provided, second-law efficiency of 7.8% • Largest irreversible losses due to dissipation of chemical exergy as low-grade heat • Evaluation and discussion of thermodynamic losses for all individual components Direct air carbon capture plants’ high energy consumption may be argued as prohibitive to their large-scale deployment. Here, Long-Innes and Struchtrup analyze the thermodynamic losses/exergy destruction at a system and component level for a natural-gas-fueled plant and discuss the loss mechanisms’ implications for process improvements and energy usage reductions.

Hydroelectric dams and power demand in Malaysia: A planning perspective

Abstract Rising energy demand and global commitment to reduce carbon emission have led to increasing share of renewable energy in electricity generation mix, particularly hydropower. In line with the global trend, Malaysia has endeavored to develop hydropower and this was demonstrated in the proposal of 12 mega dams in one single Bornean state of Malaysia under the Sarawak Corridor of Renewable Energy. Two of the dams are currently operational and one is at its early stage of construction. The mega dams have raised much doubt at their inception in view of the cumulative social and environmental impacts they could bring. Commissioning of two mega dams was immediately followed by establishment of energy-intensive plants sparking further need for energy. This article therefore aims to examine the energy supply and demand scenario and discuss the available energy options. These are achieved via desktop study and literature review. It points to a lack of planning in energy utilization in relation to the industrial expansion aspired, which gives rise to a reactive response to mounting energy demand without due consideration to other potential energy options. This contrasts the strategic energy planning practiced in developed nations and the socio-energy systems design advocated by some researchers. This article calls for consideration of natural gas, biomass residues and solar power as potential energy options as well as a strategic and participatory governance in hydropower expansion.

Effect of Perform-Achieve-Trade Policy on Energy Efficiency of Indian Industries

India adopted a Cap and Trade in energy intensity via a scheme called Perform-Achieve-Trade (PAT) with the objective to improve energy efficiency of the high energy intensive industries through target setting and tradable energy saving certificates. The scheme was announced in 2007 and the first cycle runs from April 2012-March 2015. This is the first market-based instrument adopted in India to achieve environmental protection. Under this scheme, the Bureau of Energy Efficiency identified eight most energy intensive industries, and within each of these industries it identified the most energy intensive plants and assigned them Energy Intensity (EI) targets. Firms exceeding their targets were given ESCerts which could be traded in Indian Energy Exchange and Power Exchange of India. This paper aims to examine effectiveness of the PAT scheme on inducing firms to reduce energy intensity of Cement, Fertilizer, and Pulp and Paper Industries. We use panel data for firms in the three industries with a difference-in-difference model to estimate the average treatment effect of the PAT scheme on firms that were assigned targets. We find that the PAT scheme was effective in improving energy intensity of firms in the cement and fertilizer industry, but not in the pulp & paper industry. Further, the scheme resulted in a decrease of power & fuel expenditure in the two industries, which in turn amounts to reduction of 9.53 million tC and 1.37 million tC for the cement and fertilizer industries respectively. The paper finally examines the market for ESCerts.

The spatiotemporal variation and key factors of SO2 in 336 cities across China

Sulfur dioxide (SO2) pollution has become a severe concern in China, which is closely linked to human health. Here, the officially released data of SO2 in the 336 prefecture-level cities in 2015 across the whole China were firstly collected to understand the spatiotemporal variation of the SO2 concentration. At a national scale, the SO2 concentration was highest in winter, followed by one in spring and autumn, and the lowest one in summer. The spatial econometric models, the geographical weight regression (GWR) model, and the generalized additive model (GAM) were then applied to examine the interaction of socioeconomic factors (e.g., gross domestic production (GDP)) and the meteorological indicators (e.g., precipitation) on the SO2 level in the 336 cities over China. The results suggested that the SO2 concentration was negatively associated with GDP, precipitation, wind speed (WS), and relative humidity (RH), while it showed the positive relationship with gross industrial production (GIP), population, and temperature. GDP in the Jiangsu and Zhejiang provinces presented the negative correlations with the SO2 concentration, suggesting the adaptation of industrial structure has occurred in the developed region. The positive effect of GIP on the SO2 concentration increased from West China to North China because many energy-intensive industries were concentrated on North China. The GAM analysis suggested that the combined effects of the adverse meteorological condition (e.g., RH = 50–60%) and the higher GIP contributed to severe SO2 pollution. Therefore, the SO2 emission from the heavy industries especially in NCP should be reduced and many energy-intensive plants in the region should be moved to some cities with favorable diffusion condition.

Interregional carbon emission spillover–feedback effects in China

A three-region input–output model was applied in this study to analyze the emission spillover–feedback effects across the eastern, middle, and western regions of China. Results revealed that the interregional trade has important spillover effects (SEs) on the emissions of each region, particularly in the middle and western regions, but the feedback effects are few. Although the eastern regional final demands have a smaller economic SE per unit than those of the middle and western regions in 2002–2010, its emission SE gradually exceeded that of the two other regions. The interregional trade policy has to be enforced in the future, but the emission SEs should be controlled efficiently. Therefore, the central government should continue to implement the policies on the reduction of energy and carbon intensities from the past decade, limit coal consumption, and encourage renewable fuel development. At the same time, the central government and the eastern region can help the middle and western regions control their carbon intensity by providing fiscal, technological, and training assistance. The middle and western regions should set strict admittance standards for energy-intensive plants that transferred from the eastern region.

Measuring improvement in energy efficiency of the US cement industry with the ENERGY STAR Energy Performance Indicator

The lack of a system for benchmarking industrial plant energy efficiency represents a major obstacle to improving efficiency. While estimates are sometimes available for specific technologies, the efficiency of one plant versus another could only be captured by benchmarking the energy efficiency of the whole plant and not by looking at its components. This paper presents an approach used by ENERGY STAR to implement manufacturing plant energy benchmarking for the cement industry. Using plant-level data and statistical analysis, we control for factors that influence energy use that are not efficiency, per se. What remains is an estimate of the distribution of energy use that is not accounted for by these factors, i.e., intra-plant energy efficiency. By comparing two separate analyses conducted at different points in time, we can see how this distribution has changed. While aggregate data can be used to estimate an average rate of improvement in terms of total industry energy use and production, such an estimate would be misleading as it may give the impression that all plants have made the same improvements. The picture that emerges from our plant-level statistical analysis is more subtle; the most energy-intensive plants have closed or been completely replaced and poor performing plants have made efficiency gains, reducing the gap between themselves and the top performers, whom have changed only slightly. Our estimate is a 13 % change in total source energy, equivalent to an annual reduction of 5.4 billion/kg of energy-related carbon dioxide emissions.

Cost Minimization in an Energy-Intensive Plant Using Mathematical Programming Approaches

This work addresses the problem of determining the optimal operating schedule that minimizes the operating cost in an energy-intensive air separation plant. The difficulty arises from the fact that the rate at which the utility company supplies electricity to the plant is subject to high fluctuations. This creates a potential opportunity to reduce average operating costs by changing the operating mode and production rates depending on the power costs. However, constraints occur due to product distribution requirements and plant capabilities. The scheduling optimization problem is made more challenging because the power prices are only known for a portion of the desired optimization horizon. These challenges were addressed by developing an efficient two-stage stochastic programming approach. Extensive analysis was done which resulted in a MILP problem formulation that uses an ARIMA model to generate the necessary scenarios for future power prices. The proposed problem was solved by utilizing commercial sof...