Cost Of CO2 Emissions Research Articles

Greener lightweight foam concrete using seaweed industrial by-product to replace natural sand with inorganic salt as a stabilizer

In recent years, the seaweed industry has expanded, resulting in higher volumes of seaweed industrial by-products (SWB). People commonly dispose SWB on land, which raises environmental concerns due to its hazardous chemical content. The use of waste materials as alternatives to natural sand has gained attention due to its potential to reduce environmental impact. Therefore, this study aimed to develop a greener lightweight foam concrete (LFC) by incorporating 0-30% SWB as a replacement for natural sand in fine aggregates and evaluate its performance. Furthermore, the study investigated the inclusion of inorganic salt concentrations ranging from 0 to 15% into the concrete mixture to improve performance. The production, sampling, and testing procedures followed the SNI 8640:2018 standards. Properties like density, water absorption, drying shrinkage, and compressive strength were analyzed for SWB percentage (0-30%), salt concentration (0-15%), foaming pressure (0.20, 0.39, and 0.59 MPa), and curing duration (7, 14, and 28 days). Viable specimens were further examined for microstructure, energy intensity, CO2 emission, and production cost. Specimen FS5 met standards with a density of 707.1 kg/m3, compressive strength of 2.12 MPa, water absorption of 25.45% (v/v), and drying shrinkage of 0.13%. The energy intensity, CO2 emission, and total cost of greener LFC were calculated to be 159.88 MJ/m3, 188.98 kg of CO2/m3, and IDR 682,130/m3, respectively. Ultimately, this work greatly contributes to the field of green manufacturing and environmental sustainability by successfully decreasing energy intensity, CO2 emissions, and environmental harm in LFC production processes.

RESEARCH OF THE ACTIVITIES OF PEASANT FARMS IN KAZAKHSTAN IN THE CONTEXT OF EFFECTIVE ENERGY CONSUMPTION

Some of the concepts that can be identified with agriculture in Kazakhstan include farmers and livestock breeders. Nowadays, the concept of agriculture is inextricably linked with the concepts of efficient energy consumption and "green" farming, thus there is a need to improve the use of renewable energy sources. Ensuring the efficient use of energy has advantages in the form of lower production costs and social benefits in the form of reducing carbon dioxide emissions to a level that does not harm the environment, in support of sustainable development of agricultural regions. The purpose of the article is to analyze the impact of the use of renewable energy sources on the development of peasant farms. In particular, it is planned to identify factors related to renewable energy sources in terms of agricultural development, profitability, and their impact on the environmental component. In this context, an analytical comparison of installed renewable energy capacities and indicators of reducing the cost of CO2 emissions due to energy-efficient technologies of the new generation was carried out.

Coal Phase-Out and Carbon Tax Analysis with Long-Term Planning Models: A Case Study for the Chilean Electric Power System

Large CO2 emissions constitute a significant problem today due to their effect on climate change, and the need to design appropriate energy policies to mitigate their consequences and reduce emissions requires a detailed analysis of one of the main sources of such emissions: the electricity system. Thus, this paper presents a study on the effects of energy policies on decarbonization by comparing the detailed phase-out of coal-fired power plants across a range of cases with the implementation of a carbon tax to meet Nationally Determined Contributions (NDCs). The case study focuses on the Chilean electricity system, using a long-term generation and transmission expansion planning model (GTEP) that incorporates a wide range of generation technologies. The study examines the long-term effects of these policies, including costs, investments, and CO2 emissions, as well as their impact on consumer prices reflected in the marginal costs of the system. The transmission system modeling covers various regions of Chile and significant projections for renewable energy sources. It evaluates three economic scenarios based on generation technology costs, fuel prices, and electricity demand under four different closure schemes and fourteen different carbon tax levels. The results indicate that implementing a carbon tax can be more cost-effective for the system than the implementation of a phase-out schedule for coal plants, taking the form of reduced CO2 emission and overall system costs, with an optimal carbon tax value of 37 USD/tCO2. Additionally, the study reveals significant effects on consumer prices, showing that a carbon tax as an energy policy leads to lower prices compared to a phase-out scheme.

Modification of the polymeric admixture based on polycarboxylate ether using silica-derived secondary materials obtained from fly ash and the efficiency of its application in concrete

The rising energy prices and the costs of CO2 emissions into the atmosphere are forcing the construction industry to search for ways to reduce cement consumption in concrete technology by optimizing concrete mixtures and making greater use of chemical admixtures. The scientific problem lies in understanding how polymers modified with silica-derived secondary materials, such as those obtained from fly ash (e.g., synthetic zeolites, mesoporous silica), interact with the concrete matrix and influence their durability and strength. The present study investigated the effect of a polymeric admixture based on polycarboxylic ether (PCE) modified with silica-derived secondary materials obtained from fly ash (synthetic zeolites, mesoporous silica) on the physical and mechanical properties of concrete. The study considered the effect of the modified polymer admixture dosed in 3 different amounts (0.4%, 0.8% and 1.2%) by weight of cement on the fresh properties of the concrete mixture, i.e. consistency and air content. The research scope also included determining the physico-mechanical properties of the concretes and investigating the effect of the modified admixture on the frost durability of the cement composite. In order to study the modification of the concrete microstructure, XRD phase analysis and air pore structure analysis by MIP were carried out. The study showed an increase in compressive strength after 28 days of curing in concretes containing the modified polymer of about 8-12% compared to the reference concrete. In addition, it was observed that strength increased with increasing admixture dosage. The resulting pore structure, contributed to improving the frost resistance of the concretes by reducing compressive strength loss from about 14% in reference concretes to about 2-9% in concretes with the modified polymer after 150 cycles of alternating freeze-thaw. At the same time, it was observed that the use of the modified polymer resulted in an increase in weight absorption from 2% do 4.5%, a more than twofold increase in depth of penetration of water under pressure and a more than 70% increased total porosity. In conclusion, the polymer-modified MCM-41 can positively affect the mechanical and durability properties of concrete, but it causes a change in the pore structure, which could have a negative effect on water absorption and total porosity.

Introduced Iron-Based Catalysts for Low-Temperature Upcycling Regeneration of Spent Graphite towards Ultra-Fast Lithium Storage Properties.

Spent graphite, as the main component of retired batteries, have attracted plenty of attentions. Although a series of recycling strategies are proposed, they still suffer from high cost of regeneration and large CO2 emission, mainly ascribed to the full-recovery of surface and internal phase at ultra-high temperature. However, the existing of suitable internal defects is conductive to their energy-storage abilities. Herein, with the introduction of Fe-based catalysts, spent graphite is successfully repaired at low temperature with the tailored surface traits, including conductivities, isotropy and so on. As Li-storage anodes, all of samples can display a capacity of 340mAhg-1 above at 1.0 C after 200 cycles. At high rate 5.0 C, their capacity can be also kept ≈300mAhg-1, and remained ≈233mAhg-1 even after 1000 cycles. Assisted by electrochemical and kinetic behaviors, their cycling traits with dynamic surface transformations are detailed explored, including activated/fading mechanism, Li-depositions forming etc. Moreover, the calculated constant time of as-optimized regenerated sample is ≈3.0×10-4s, further revealing the importance of surface designing. Therefore, the work is expected to shed light on their energy-storage behaviors, and offer low-temperature regenerated strategies of spent graphite with high value.

Energy comparison and cost estimation of pressure-retarded osmosis using spiral wound membrane

Advancements in Pressure Retarded Osmosis (PRO) technology are enhancing the feasibility of evaluating its economic viability against other renewable energy production methods. This is done using the Levelized Cost of Energy (LCOE) as a metric. The study focuses on three PRO scenarios designed to minimize environmental impact and promote sustainable energy. These scenarios utilize a spiral-wound membrane module combined with hyper-saline solutions from Reverse Osmosis (RO) and wastewater from demineralization processes. Experimental results using a commercial spiral-wound membrane in the PRO system yielded LCOE values of USD 0.0702/kWh for a draw solution (DS) concentration of 36.2 g/l, USD 0.0563/kWh for 44.2 g/l, and USD 0.0721/kWh for 51.8 g/l. The study also evaluated environmental viability by considering the cost of CO2 emissions. This comprehensive comparison highlighted PRO's competitiveness with fossil fuels, showing it to be a reasonable alternative to coal and oil but less practical than natural gas. Specifically, the environmental analysis revealed that PRO is approximately 25.2 % more competitive than coal and 9.76 % more competitive than oil but 27.16 % less competitive compared to natural gas in terms of CO2 emission costs. This underscores the importance of considering carbon emission mitigation in energy generation.

Thermo-economic analysis and comparison of novel desiccant air conditioning systems

Desiccant air conditioning (DAC) systems are considered an effective alternative to traditional vapor compression systems due to their ability to independently control temperature and humidity, coupled with their environmentally friendly design. Consequently, this paper deals with experimental and simulation study on DAC systems. The experiments were conducted on a reference system (RS) equipped with all necessary control and measurement devices. This reference system includes a traditional desiccant evaporative air-conditioning system with an additional heat exchanger placed after the desiccant wheel, functioning as an after-cooler. In addition, steady state and transient simulation models were developed using TRNSYS software to predict the performance of four different configurations of DAC systems and the reference system, under hot and humid climatic conditions.The experimental data verify the precision and relevance of the simulation results, with an average error of 2.57 % for the air temperatures. The steady state findings showed that Config-4 exhibited the best thermal performance compared to the other configurations. Also, Config-4 demonstrates a stable thermal cooling capacity despite fluctuations in outdoor air dry-bulb temperature. Transient results revealed that, Config-4 has levelized costs of CO2 emissions that are 64.2 % lower than RS, followed by Config-3, Config-2, and Config-1. Lower CO2 emissions result in a positive impact on mitigating climate change and improving air quality. Economic analysis revealed that the total levelized cost of cooling (LCOC) for Config-4 is 70.5 % lower than RS, demonstrating the most significant cost reduction. Configurations 3, 2, and 1 also showed lower LCOC compared to the reference system.

Enhancing the integration of PV and coal-fired power plant for low-carbon, low-cost, and reliable power supply through various energy storage systems

The integration of photovoltaic (PV) system and coal-fired power plants (CFPP) through various energy storage systems (ESS) presents a promising strategy for achieving a low-carbon, low-cost, and reliable power supply. This study proposes a low-carbon power system that deeply integrates PV and CFPP through battery, thermal, and ammonia energy storage system (BESS, TESS, AESS). Multi-objective optimizations were conducted to minimize both the levelized cost of electricity (LCOE) and specific CO2 emission while considering constraints related to power supply reliability. Additionally, the influence of technological advancements on reducing LCOE was explored, providing insights into the developmental pathways of these energy storage technologies. The results indicate that: (1) The optimal selection of ESS is related to CO2 emission reduction targets. For less restrictive targets, it is economical to abandon ESS and rely entirely on PV and CFPP. As emission reduction targets progress, TESS becomes economically optimal. In scenarios with strict targets, BESS becomes economically optimal. (2) The combination of PV+CFPP+MultiESS demonstrates superior cost-effectiveness under high-reliability constraints, exhibiting a 7.6 % lower LCOE compared to PV+CFPP+SingleESS at a reliability level of ≥ 99 %. (3) Compared to CFPP retrofitted with CCS, the PV+CFPP+ESS integrated system is more economically favorable for less restrictive CO2 emission reduction targets. However, as the CO2 emission limits become stricter, the CCS-retrofitted technology becomes more economically favorable. (4) To enhance cost-competitiveness, developments should be directed toward reducing the unit investment cost of storage for BESS, while reducing the unit investment cost of power conversion system for AESS. As for TESS, technological advancements across various aspects can effectively contribute to its cost-competitiveness.

Coordinated optimization of configuration and operation of a photovoltaic integrated building cooling system with electricity and ice storages under source-load uncertainties

Solar photovoltaic integration into buildings provides an effective and attractive method to decrease fossil energy consumption and reduce greenhouse gases emission. This study proposes a flexible photovoltaic integrated building cooling system with electricity and ice storages to address the challenges posed by the instability of solar energy and the integration and coordination of multiple components. Uncertainties in solar irradiance, ambient temperature, and cooling load are characterized using a scenario analysis method that combines Latin Hypercube Sampling and the K-Means++ algorithm. Then, aiming to achieve the minimal total cost, including investment, operational, and CO2 emission costs, a two-layer stochastic optimization model is developed to simultaneously determine the optimal capacities and operational strategies for each device. Genetic algorithm and mixed integer linear programming are, respectively, used to solve the two-layer optimization problem. The comparisons between optimum schemes with and without CO2 emission cost demonstrates that when the base chiller’s capacities are 1179 kW and 1081 kW in cases 1 and 2 respectively, it can independently meet 72.37 % and 61.27 % of the cooling load demand throughout the cooling season. In addition, the optimal capacity of photovoltaics, considering CO2 emission, increases by 109.7 %, and its penetration rate reaches 18.3 %, which is 9.7 % higher than the optimal scheme not considering CO2 emission. However, the annualized investment cost increases by 52.3 %. The developed methods provide effective tools for the system design and operation management of solar energy integrated building cooling system.

Techno-economic evaluation of GHG emissions mitigation of biomethane upgrading technologies

The current trend in the European biogas industry is to shift away from electricity production towards the production of biomethane for the need to replace natural gas. The upgrading of biogas to biomethane is normally performed by separating the biogas in a stream containing natural gas grid quality methane and a stream containing mostly CO2. The CO2 stream is normally released into the atmosphere; however, part of the methane may still remain in it, and, if not oxidized, even a small fraction of methane released may jeopardise all the GHG emissions savings from producing the biomethane, being methane a powerful climate forcer. Scope of this work is to assess the opportunity cost of installing an Off Gas Combustion (OGC) device in biomethane upgrading plants. The currently available technologies for biogas upgrading to biomethane and the most common technology of OGC (the Regenerative Thermal Oxidisers, RTO) are described according to their performances and cost. Then the cost per tonne of CO2eq avoided associated to the adoption of RTO systems in relation to the upgrading performance is calculated to identify a potential threshold for an effective and efficient application of the RTO systems. It is found that, in case of upgrading technologies which can capture almost all biomethane in the upgrading off-gas (i.e. 99.9%), currently the adoption of an RTO to oxidise the methane left in the off-gas would add costs and need additional fuel to be operated, but would generate limited GHG emission savings, therefore the cost per tonne of CO2eq emissions avoided would result not competitive with other GHG emissions mitigation investments. While the installation of RTOs on upgrading systems with a methane slip of 0.3%, or higher, normally results cost competitive in reducing GHG emissions. The installation of an RTO on systems with a methane slip of 0.2% results in a cost per tonne of CO2eq emissions avoided of 50–100 euro, which is comparable to the current cost of CO2 emissions allowances in the EU ETS carbon market, representing therefore a reasonable choice for a threshold on methane slip regulation for biogas upgrading systems.

Economic optimization of hybrid renewable energy resources for rural electrification

In rural areas, grid expansions and diesel generators are commonly used to provide electricity, but their high maintenance costs and CO2 emissions make renewable energy sources (RES) a more practical alternative. Traditional methods such as analytical, statistical, and numerical-based techniques are inadequate for designing an energy-efficient RES. Therefore, this study utilized the bat algorithm (BA) to optimize the use of hybrid RES for rural electrification. A feasibility study was conducted in the village of Kalema to assess energy consumption, and a diesel-only system was modeled to serve the entire community. The BA was used to determine the optimal size and cost-effectiveness of the hybrid RES, with MATLAB R (2021a) utilized for simulation. The BA's performance was compared with diesel only and GA using cost of energy (COE) and CO2 emissions as metrics. Diesel generators only produced a COE of $6,562,000 and 1679.6 lb/hr of CO2 emissions. COE with BA was $356,9781.37 (a 45.6% reduction) and CO2 emissions were 635.29 lb/hr (a 62.2% drop). Genetic algorithm (GA) resulted in $364,3122.46 COE and 652.69 lb/hr CO2 emissions, indicating 61.1% and 44.5% decreases, respectively. BA significantly reduced COE and CO2 emissions over GA, according to the analysis.

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

A Combined Ranking and Sensitivity Analysis of Power Generation Using Multi-Criteria Decision-Making and Monte-Carlo Simulation

This research examined energy sources that can be employed in a region to assist policymakers in determining energy priorities. Three key components were analyzed in this research to rank these energy sources: Levelized Cost of Energy (LCOE), CO2 emissions, and power density. A combination of multi-criteria decision-making (MCDM) methods, namely the Analytical Hierarchy Process (AHP)-Entropy-the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was used to assess these criteria, which had not been previously applied to rank energy sources. Additionally, the Monte-Carlo method was utilized to detect changes in sensitivity throughout the rankings. Results of the study indicated that gas energy topped the list, followed by Solar Photovoltaic (PV)-crystalline, geothermal, wind, nuclear, Solar PV Commercial & Industrial (C&I), Solar Thermal Tower with Storage, and residential PV rooftop solar. Moreover, nuclear energy ranked the highest when looking at the sensitivity of parameters, while utility-scale Solar PV and wind energy ranked the next highest. Thus, this research can be used to increase objectivity in the assessment and selection of power generation technology to be implemented.

Techno-economic feasibility of integrating hybrid battery-hydrogen energy storage system into an academic building

Green hydrogen production and storage are vital in mitigating carbon emissions and sustainable transition. However, the high investment cost and management requirements are the bottleneck of utilizing hybrid hydrogen-based systems in microgrids. Given the necessity of cost-effective and optimal design of these systems, the present study examines techno-economic feasibility of integrating hybrid hydrogen-based systems into an outdoor test facility. With this perspective, several solar-driven hybrid scenarios are introduced at two energy storage levels, namely the battery and hydrogen energy storage systems, including the high-pressure gaseous hydrogen and metal hydride storage tanks. Dynamic simulations are carried out to address subtle interactions in components of the hybrid system by establishing a TRNSYS model coupled to a Fortran code simulating the metal hydride storage system. The OpenStudio-EnergyPlus plugin is used to simulate the building load, validate against experimental data, according to the measured data and monitored operating conditions. Aimed at enabling efficient integration of energy storage systems, a techno-enviro-economic optimization algorithm is developed to simultaneously minimize the levelized cost of the electricity and maximize the CO2 mitigation in each proposed hybrid scenario. The results indicate that integrating the gaseous hydrogen and metal hydride storages into the photovoltaic-alone scenario enhances 22.6% and 14.4% of the annual renewable factor. Accordingly, the inclusion of battery system to these hybrid scenarios gives a 30.4% and 20.3 % boost to the renewable factor value, respectively. Although the inclusion of battery energy storage into the hybrid systems increases the renewable factor, the results imply that it reduces the hydrogen production rate via electrolysis. The optimized values of the levelized cost of electricity and CO2 emission for different scenarios vary in the range of 0.376–0.789 $/kWh and 6.57–9.75 ton, respectively. The multi-criteria optimizations improve the levelized cost of electricity and CO2 emission by up to 46.2% and 11.3%, with respect to their preliminary design.

A flexible and deep peak shaving scheme for combined heat and power plant under full operating conditions

Improving the flexible and deep peak shaving capacity of combined heat and power (CHP) plant under full operating conditions to facilitate renewable energy consumption is the main choice of novel power system. Accordingly, a dry/wet state automatic conversion control scheme fuses the precise mechanism structure, reinforcement learning and multi-objective model predictive control (MPC) algorithms is designed to promote the deep peak shaving ability of CHP plant in this paper. Firstly, the detailed mechanism models of once-through boiler at dry and wet state are presented by analyzing the dynamic characteristics of steam-water flow. Secondly, the large-scale unknown parameters in mechanism models are identified via the Takagi-Sugeno fuzzy modeling, reinforcement learning algorithms and actual dry/wet state conversion data. Thanks to the proposed hybrid modeling strategy, the high-precision boiler-steam unit models at dry and wet state are rapid obtained. Then, to meet different peak shaving demands, the multi-objective MPC algorithm is respectively constructed under dry and wet state with the comprehensive consideration of operational constraints, load tracking error, algorithm stability, power generation cost, CO2 and NOx emission costs. Aiming at maximizing the peak shaving efficiency and flexible operation ability of plant, a dry/wet automatic control scheme combined the designed multi-objective MPC algorithms and identified dry/wet state models is proposed. Finally, the load variation rate of 5 % and 2 % RCM/min is respectively achieved in the dry/wet state conversion tests on a 350 MW CHP plant based on the proposed control scheme. Thus, the rapid and thorough dry/wet state conversion performance of once-through boiler has successfully improved the operational flexibility of CHP plant under full operating conditions.

Decarbonization of simulated biogas with microchannel mixer by pressurized water scrubbing

Pressurized water scrubbing is an environmentally friendly technology for the decarbonization of biogas. However, the key bottlenecks such as low efficiency, high cost of water consumption and secondary CO2 emission by water absorption and desorption in the process of decarbonization are still necessary to be solved. This study focused on improve the mass transfer effect by introduce finger-crossed microchannel in the process of simulated biogas decarbonization using pressurized water scrubbing. The simulated biogas was mixed with pressurized water in the finger-crossed microchannel, and the gas-water mixture was continuously separated in the gas-water separation tank. The effects of pressure (26–30 bar), temperature (5–30 °C), gas-water ratio (5:1–12:1), liquid volumetric flowrate (5–10 mL/min), and other factors on the decarbonization were investigated. The overall mass transfer coefficient based on the liquid phase and the CO2 flux were also calculated and analyzed. The decarbonization parameters were optimized using the response surface methodology as follows: temperature 20 °C, pressure 29/27 bar, gas-water ratio 10:1, liquid volumetric flowrate 5 mL/min. The process remained stable, achieving 98 % removal of CO2 under optimal conditions. Furthermore, the CO2 concentration in the purified gas was maintained below 3 %. Additionally, a significant number of micro-nano bubbles were observed in the absorption water obtained through this mixer, and the releasing of CO2 from the water lasted 5 days. These results indicated the excellent decarbonization performance of the finger-crossed microchannel in pressurized water scrubbing and potential application value of new ways of CO2 absorption water without desorption.

Distributed robust scheduling optimization for energy system of steel industry considering prediction uncertainties

Predictive scheduling is commonly deployed for the energy systems in the steel industry, while the uncertainties caused by the predictions can lead to under-optimization or over-adjustment. In order to solve this problem, a novel distributed robust optimization framework is proposed in this study. A Robust Optimization (RO) model is established at first to mathematically address the prediction uncertainties, where the gas, steam, and electricity networks are considered as distributed participants, with their operating costs and CO2 emissions costs as the objectives for minimization. Then the vanilla 2-block Alternating Direction Multiplier Method (ADMM) is extended to a 3-block structure in this study for solving the established RO model in a distributed manner. Considering the superiority on efficiency, the Column-and-Constraint Generation (C&CG) algorithm is deployed for each block. To ensure convergence considering the extensive interaction between the updated dual and coupling variables in each iteration of the overall ADMM and each C&CG, an adaptive bridging method is developed in this study. Finally, experiments using real data from a steel plant in China demonstrate that the proposed framework has a deviation of less than 1.33 % while with higher efficiency and better robustness compared to other algorithms.

The Potential of Renewable Energy to Replace Diesel Power Plants in Supporting Energy Transition in Indonesia

The Indonesian government is committed to reducing greenhouse gas emissions under the Paris Agreement. One form of this commitment is the program to replace diesel power plants with renewable energy plants in the electricity sector. Fossil-based diesel power plant operations have disadvantages, such as relatively expensive generation costs and greenhouse gas emissions. There are three renewable energy technology options as potential substitutes for diesel power plants: a solar photovoltaic (PV) power plant integrated with a battery energy storage system (BESS), a small-scale geothermal power plant, and a micro-hydropower plant. This paper will analyze the prospects of each technology option based on its economic and environmental impact. Various technical parameters, including renewable energy potential and intermittent factors, as well as economic parameters such as investment and generation costs, are important factors for selecting prospective renewable energy generators. The analysis was carried out by calculating the levelized cost of electricity (LCOE), CO2 emissions, and oil fuel consumption for four different scenarios. The results of the analysis show that replacing the diesel power plants with micro-hydropower plants can reduce LCOE by 0.24 USD/kWh to 0.12 USD/kWh. The use of a solar PV power plant integrated with a BESS has the most potential to reduce CO2 emissions, which account for 54% of emissions from diesel power plants. Meanwhile, the potential for oil fuel reduction from this program can reach an annual average of 0.85 million kl.

Optimal design and sizing of a hybrid energy system for water pumping applications

AbstractOne of the ways to increase the participation and penetration of renewable energy resources is to bring down the cost of these abundant resources for easy implementation and affordability. In this paper, a generalized reduced gradient (GRG) non‐linear optimization algorithm is implemented to solve a tri‐objective optimal design and sizing of a low‐cost hybrid mix consisting of a photovoltaic (PV) power plant, biomass power plant (BPP), and battery energy system for water pumping load applications in the University of Johannesburg, South Africa considering four different hybrids of biomass‐battery, PV‐battery, PV‐biomass, and PV‐biomass‐battery. The optimization model considers available energy and battery state of charge while minimizing least cost of energy (LCOE), carbon dioxide emission (tCO2eq), and loss of power supply probability (LPSP) including carbon tax incentive and penalty. The results when compared against particle swarm optimization (PSO) show the superiority of GRG over PSO with an optimal combination of PV‐biomass‐battery mix with optimal size of the PV power plant as 360.50 kW, the BPP 181.08 kW, and the battery size of 6,553.60 kWh giving a minimal optimal LCOE, CO2 emission and LPSP of 0.018 $/kWhr (with carbon tax), and 0.016 $/kWhr (without carbon tax), 28,067.73tCO2eq tCO2eq, and 1.7%, respectively. These values give a competitive advantage compared to the unit cost and values of CO2 emission and LPSP currently in the literature.

CO2 emission evaluation and cost analysis of oxygen blast furnace process with sintering flue gas injection

CO2 emission evaluation and cost analysis of oxygen blast furnace process with sintering flue gas injection