Minimum Generation Research Articles

Multi-objective operation optimization analysis based on distributed energy sources

In the context of the determination and implementation of the dual carbon goal, it is an important trend of China’s energy strategy to incorporate a considerable proportion of renewable energy into the power grid. Therefore, energy consumption is gradually turning to new energy sources such as wind energy and wind energy. Considering the limitations of random, intermittent and anti-peak regulation of energy forms such as wind and light, a multi-objective optimization model of wind, light, fire and storage combined power generation and heating is built. This model can fine-tune and fill the valley by using the peak regulating capacity of thermal power plants and pumped storage devices, so that the whole system has stable power generation and heating capacity. The model is solved by multi-purpose particle swarm optimization algorithm based on maximum total generation and heating rotation and minimum generation and heating slope fluctuation. The calculation results show that the established model can effectively improve the wind and light consumption rates and reduce the peak set pressure of the thermal device.

Biohydrogen production from starchy wastewater in upflow anaerobic sludge blanket (UASB) reactor: Possibilities toward circular bioeconomy

The present study investigates the performance of upflow anaerobic sludge blanket (UASB) reactor for stable H2 production from starchy wastewater supplemented with groundnut de-oiled cake using mixed consortia. Insufficient reports are available on H2 production for UASB reactor. Operation of the UASB reactor was divided into two stages i.e., start-up period where desirable sludge height was developed and production period where different hydraulic retention time (HRT) was examined for H2 production. The maximum H2 production rate of 12.3 L L−1 d−1was observed at 3 h HRT. Details physicochemical characteristics of the granular sludge were studied using SEM-EDX image, FTIR spectra, particle size analyser, SVI value, EPS and metal content. Kinetic analysis of the process revealed that Grau, and modified Stover-Kicannon were the most suitable for H2 producing UASB reactor. This is the first report to implement these advanced bio-kinetic models of substrate consumption on hydrogen production in UASB reactor. Furthermore, a potential toward circular bioeconomy model has been discussed for the accomplishment of maximum resource recovery with a minimum waste generation.

Binding constraints를 고려한 딥러닝 기반 최적조류계산 모델 및 대형계통 적용 사례 연구

Recently, research using machine learning and deep learning is being conducted to quickly solve the AC optimal power flow (AC OPF) problem. The problem with the existing research is that, unlike the actual system, it did not consider the generator start-up status according to demand change by using a test system in which the minimum power generation of the generator is zero. This paper proposes a deep learning-based AC OPF model and post-processing for a simulated large-scale system in Korea. It is a difficult problem to predict in Korea

Design and operational optimization of a methanol-integrated wind-solar power generation system

Wind and solar energy are rapidly being merged into electricity grids in China. High penetration of variable renewable electricity drives the development of energy storage with low cost, high flexibility and utility-scale. To this end, a methanol-based energy storage system is proposed to meet regional power demand by combining a hybrid wind-solar source. This work studies capacity configuration and logistics scheduling at the hourly level with the minimum power generation cost. The round-trip efficiency reaches 41.5%, and the levelized cost of electricity is 0.148 $/kWh. The wind-solar hybrid system improves the system efficiency and economy compared with separated wind or solar systems. Taking methanol as the hydrogen carrier significantly reduces the storage scale of hydrogen. In terms of regions with larger fluctuation of renewable energy, methanol-based energy storage is more cost-effective than hydrogen energy storage.

Exergoeconomic and Exergetic Sustainability Analysis of a Combined Dual-Pressure Organic Rankine Cycle and Vapor Compression Refrigeration Cycle

In this paper, an exergoeconomic and exergetic sustainability analysis of a dual-pressure organic Rankine cycle (ORC) and vapor compression refrigeration cycle (VCRC) driven by waste heat is performed for power generation and cooling production. In addition, the most suitable fluid couple among the thirty-five different fluid pairs was investigated for the proposed combined system. The results indicate that the highest energy utilization factor, exergy efficiency, the system coefficient of performance, and net power are calculated for the R123-R141b fluid pair. In terms of exergetic sustainability indicators, the best performance results are obtained for the R123-R141b fluid combination. The minimum unit electricity generation cost and the shortest payback period are calculated as 0.0664 $/kWh and 2.5 years, respectively, for the R123-R290 fluid pair. The system component with the highest exergy destruction is the boiler, with 21.67%. The result of the parametric analysis showed that the thermodynamic performance parameters increase with the increment of the ORC’s boiling temperature. In addition, with the increasing boiling temperature, the environmental effect factor of the system decreases, while the exergetic sustainability index increases. Additionally, as the boiling temperature increases, the total system cost increases, while the unit electricity production cost and payback period decrease. It is suggested to use a R123-R141b fluid couple among fluid pairs created as a result of thermodynamic, exergoeconomic and sustainability analysis.

Multi-operation state traction control of regional coal-fired and gas-fired combined power generation system

The traditional dispatching model and strategy of coal-fired and gas-fired power units are difficult to take into account the minimum total cost of power generation and the stable output of each unit. Therefore, this paper proposes a staged traction control model of coal-fired and gas-fired combined power generation, aiming at the minimum total power generation cost and stable output of the units. Based on the safe operation constraints of the regional coal-fired and gas-fired combined power generation system, the particle swarm optimization algorithm is adopted to solve the traction control strategy of the regional coal-fired and gas-fired combined power generation system in multiple operation states. The example simulation shows that the traction control strategy of regional coal-fired and gas-fired combined power generation systems in multiple operating states can realize flexible, coordinated control of each unit. Based on quickly responding to the change in load demand, it meets the minimum total power generation cost of regional coal-fired and gas-fired combined power generation systems. It makes the unit output stable to prolong the service life of the unit.

Electricity Cost Reduction of Industrial/General Purpose Customers in Sri Lanka using Solar PV and Battery Storage

Many solar installations are coming up to harness solar electricity in Sri Lanka, including on rooftops. Since the Industrial and Commercial customers are crucial for the economic activities, utility providers have introduced several tariff schemes for financial motivation to go for Solarphotovoltaics. However, with rooftop Solar PV systems, the management of excess solar generation has become a challenge for the utility provider who shed the excess solar generation to regulate the grid parameters. As a result, return of investment for the rooftop solar systems has been reduced drastically for industrial purpose(IP) and general purpose (GP) customers in Sri Lanka. The real time management of the PV generation can be conducted with the available Loads and the other generating sources, like Diesel Engines and Battery Storage. The maximum demand cost needs to be considered and the unit costs can be calculated based on the LCOE technique to reflect the lifetime costs of each source and optimization technique can be used to dispatch the generation and loads based on the optimum cost. In this paper, the PV generation optimization of Industrial Purpose/ General Purpose customers has been conducted using quadratic optimization technique to reduce the electricity cost. The results of the study show that for two selected GP and IP consumers, the program derives the optimum size of battery capacity for a given installation and the minimum solar generation requirement for the economic benefit.

Design and techno–economic analysis of levulinic acid production process from biomass by using co-product formic acid as a catalyst with minimal waste generation

Levulinic acid (LA) is an essential biomass-derived platform chemical that can be converted into value–added chemicals such as polymers, fertilisers, and pharmaceuticals. However, the high energy demand and cost required in the separation process are significant issues in the LA production process. Recently, formic acid (FA), the co–product in biomass–LA reaction, has been focused on as a catalyst for both biomass pretreatment and LA production. This study designed and numerically simulated a novel process for producing LA from wheat straw (feed rate: 100 kg/h) using an FA aqueous catalyst system (60, 70, and 80 wt%). The reaction data were referred to previous kinetics studies in order to evaluate the feasible reaction time from an economic perspective. The minimised waste generation process was designed by recovering the FA catalyst and using solid residues (lignin and humins) as heat sources. Another byproduct, furfural, was utilised as an extractant for purifying the LA and recovering unreacted products. The minimum selling price (MSP) of the LA and furfural was calculated with an internal rate of return of 6.1% for 20 years. The MSPs were calculated to be 9.59–12.8 USD/kg–products, which was higher than the market price and previous studies. However, the net required energy in this process was − 5.37 to − 32.1 MJ/kg–LA, indicating that the combustion of the solid residue can supply all of the energy required for the process. Our novel concept based on the byproduct utilisation for heat source and extractant can be an effective strategy for an implication of the biorefinery process that can circulate energy with minimum waste generation.

Minimum Dynamic Cable Tension Workspace Generation Techniques and Cable Tension Sensitivity Analysis Methods for Cable-Suspended Gangue-Sorting Robots

The separation of gangues from coals with robots is an effective and practicable means. Therefore, a cable-suspended gangue-sorting robot (CSGSR) with an end-grab was developed in our early work. Due to the unidirectional characteristic, the flexibility of cables, and the dynamic impact of pick-and-place gangues, one of the significant issues with the robots is robustness under internal and external disturbances. Cable tensions, being the end-grab’s constraints, have a crucial effect on the robustness of the CSGSR while disturbances are on. Two main issues related to the CSGSR, as a result, are addressed in the present paper: minimum dynamic cable tension workspace generation and a sensitivity analysis method for the dynamic cable tensions. Firstly, the four cable tensions and minimum dynamic cable tension while the end-grab was located at an arbitrary position of the task space were obtained with the dynamics of the CSGSR. In addition, with the dynamics of the CSGSR, a minimum dynamic cable tension workspace (MDCTW) generating approach is presented, where the minimum dynamic cable tensions are greater than a preset value, therefore ensuring the robustness of the end-grab under the disturbances. Secondly, a method for dynamic cable tension sensitivity (DCTS) of the robots is proposed with grey relational analysis, by which the influence degree of the end-grab’s positions on the four dynamic cable tensions and the minimum dynamic cable tensions was considered. Finally, the effectiveness of the proposed MDCTW generation algorithm and the DCTS analysis method were examined through simulation on the CSGSR, and it was indicated that the proposed MDCTW generation algorithm and the DCTS analysis method were able to provide theoretical guidance for pick-and-place trajectory planning and generation of the end-grab in practice.

Двухфазный рост бактерий при использовании растительного масла в качестве единственного субстрата

The growth of four bacterial strains isolated from vegetable oil samples (Mp-2 Bacillus pumilus, Mp-4 Bacillus atrophaeus, Mp-6 Sphingomonas aurantiaca and Mp-7 Microbacterium oxydans) in vegetable oil at +7°C was studied. The previously isolated soil strain Mn5 of Rhodococcus erythropolis, capable of using vegetable oil as the only substrate, was used as an object for comparison. All strains showed the ability to grow in vegetable oil with a minimum generation time of 3.5 hours (Bacillus pumilus MP-2 strain) to 14.9 hours (Bacillus atropheus MP-4 strain). In most cases, the bacterial growth curves had two peaks, that is, they corresponded to biphasic growth. Two models are proposed to explain the observed growth curves. Keywords: VEGETABLE OIL, BACILLUS PUMILUS, BACILLUS ATROPHAEUS, SPHINGOMONAS AURANTIACA, MICROBACTERIUM OXYDANS, RHODOCOCCUS ERYTHROPOLIS, BIPHASIC GROWTH, COMPUTER MODELING

Selective extraction of Sm from LiCl-KCl molten salt into wasteforms via liquid bismuth

The electrorefining of spent nuclear fuels in a molten LiCl-KCl salt electrolyte recovers the valuable actinides but also releases radioactive fission products in the salt. To minimize the nuclear waste volume, dissolved fission products such as rare earths (REs) must be removed from the electrorefining salt and immobilized into proper wasteforms. Here we propose a two-step approach for treating the electrorefining waste salt by (i) the electrolytic recovery of REs from the salt using a liquid metal cathode; and subsequent (ii) oxidative extraction of REs from the liquid metal into durable wasteforms. Experimental demonstration using rare earth element samarium (Sm) and liquid metal (Bi) was successful. The Sm ions dissolved in the salt can be selectively recovered as dendrite Sm-Bi intermetallic products on the top of liquid bismuth cathode through electrolysis at appropriate applied currents or potentials. Then the Sm in the Sm-Bi alloy was efficiently extracted into both zinc-in-titania (ZIT) glass ceramic and lanthanide aluminoborosilicate (LABS) glass wasteforms through selective oxidation at Sm2O3 loadings of 18–25 wt% and 50 wt%, respectively. Recycling of the electrorefining salt with minimum nuclear waste generation is foreseeable with the use of this simple, efficient, and highly compatible process.

Need for speed: a breakthrough speed breeding protocol for hemp

Need for speed: a breakthrough speed breeding protocol for hemp

Adaptive optimal energy management in multi-distributed energy resources by using improved slime mould algorithm with considering demand side management

In this article, a stochastic programming model is developed to solve a multi-renewable sources-based energy management with the help of a multi-objective improved slime mould algorithm (MOISMA). As a result, the microgrid's performance is expected to improve with this technique. However, such a fast-acting methodology reduces operating generation costs and emissions by using multiple renewable sources. Firstly, Hong's (2 m + 1) point estimate method is used to generate as well as control the uncertainty of wind speed and solar irradiance patterns. Secondly, this MOISMA-based-energy management study outperforms better when compared with multi-objective genetic algorithms (MOGA) and particle swarm optimization (MOPSO). All these performances are carried out at the time of use (ToU) based on demand response (DR) load management. Using these techniques, which can reduce the cost of generating power and increase energy resource use, a demand-side management study can be performed within 24 h of the generation of load data for analysis purposes. So, in this research by the application of demand-side management, we get a minimum generation of power costs and reduce the environmental emission by 12.62% and 7.43%, for wind energy, similarly 31.53% and 2.51% for solar energy systems with this DR technique. Thus, overall, it has been validated that using such a novel optimization-based energy management study can reduce system generation cost, energy usage, peak demand shifting, and environmental emissions.

Multi-Objective Optimal Long-Term Operation of Cascade Hydropower for Multi-Market Portfolio and Energy Stored at End of Year

Taking into account both market benefits and power grid demand is one of the main challenges for cascade hydropower stations trading on electricity markets and secluding operation plan. This study develops a multi-objective optimal operation model for the long-term operation of cascade hydropower in different markets. Two objectives were formulated for economics benefits and carryover energy storage. One was to maximize the market utility value based on portfolio theory, for which conditional value at risk (CVaR) was applied to measure the risk of multi-markets. Another was the maximization of energy storage at the end of a year. The model was solved efficiently through a multi-objective particle swarm optimization (MOPSO). Under the framework of the MOPSO, the chaotic mutation search mechanism and elite individual retention mechanism were introduced to diversify and accelerate the non-inferior solution sets. Lastly, a dynamic updating of archives was established to collect the non-inferior solution. The proposed model was implemented on the hydropower plants on the Lancang River, which traded on the Yunnan Electricity Market (YEM). The results demonstrated non-inferior solution sets in wet, normal and dry years. A comparison in solution sets revealed an imbalanced mutual restriction between objectives, such that a 2.65 billion CNY increase in market utility costs a 13.96 billion kWh decrease in energy storage. In addition, the non-inferior solution provided various schemes for actual demands based on other evaluating indexes such as the minimum output, power generation and spillage.

Minimum Generation Cube Matching Algorithm Based on Improved Matching Cost and Mean Segmentation

Minimum Generation Cube Matching Algorithm Based on Improved Matching Cost and Mean Segmentation

Exhaust Smoke Validity of Vertical Shaft in Restrooms using the Stack Effect

This study is performed to validate a quantitative relationship between the exhaust rate through vertical shaft, which are used for restroom ventilation, and smoke generation based on NFSC 501. The exhaust rate is calculated using heat balance equations and is based on the input and exhaust air temperatures. The neutral plan in the vertical shaft was formed at approximately 46% of the total height. Because the smoke that is exhausted through the vertical shaft is more than 20% of the minimum smoke generation suggested by NFSC 501, the smoke exhaust through the vertical shaft is considered to be possible.

Day-ahead economical planning of multi-vector energy district considering demand response program

Increasing technology developments and economic considerations have also made the use of renewable energy sources (RESs) and energy storage systems (ESSs) inevitable. To achieve the holistic planning of a microgrid consisting of several energy resources, this paper proposes a novel multi-vector energy system based on electricity, heating, and water generation sources. To supply electrical energy from heat generation units, a water-power nexus (WPN), an ESS, photovoltaic (PV) sources, and a combined heat and power (CHP) system are used. Considering the importance of Hydro generation in planning, combined energy-water and water-only systems are used to supply water demand, while heat-power and heating generation systems are used to supply heating. To make the model more realistic, the effects of the valve point, maximum and minimum generation constraints, increasing/decreasing rate, energy, water, and heating demand balance were taken into account. The main objective function of this study was to minimize multi-vector energy system costs in 24 h. To promote demand-side performance, the price-based demand response program was used to reduce the final costs in the entire study period. The proposed models have been formulated as a mixed-integer linear problem solved by the CPLEX solver in GAMS. Simulation results show that the use of RES and their proper management can reduce the generation of a thermal generator, which reduces the costs considerably. With the demand response program, the costs were reduced by 1.03%. This paper presents a systematic method for optimal system control that can provide a regulatory basis for the use of integrated generation sources.

Fervidobacterium pennivorans subsp. keratinolyticus subsp. nov., a Novel Feather-Degrading Anaerobic Thermophile.

Fervidobacterium pennivorans subsp. keratinolyticus subsp. nov. strain T was isolated from a terrestrial, high-altitude hot spring in Tajikistan. This strain is an obligate anaerobic rod and their cells occur singly, in pairs, or as short chains under the optimal growth conditions of a temperature of 65 °C and pH 6.5, with peptone, glucose, and galactose as the preferred substrates. The minimum generation time of this strain is 150 min. Strain T can efficiently degrade feather keratin at 65-75 °C; this unusual feature is also exhibited by a few other members of the Fervidobacterium genus. The total genome size of this bacterial strain is 2,002,515 base pairs, with a C + G content of 39.0%. The maximum digital DNA-DNA hybridization (dDDH) value of 76.9% was observed on comparing the genome of this strain with that of Fervidobacterium pennivorans type strain DSM9078. This study describes the physiological and genomic properties of strain T, with an emphasis on its keratinolytic power and differences from other members of the genus Fervidobacterium.

Three-Dimensional Hydrodynamic Analysis of a Flexible Caudal Fin

A 3D fluid–structure coupled simulation of a square flexible flapper, the basic model of a caudal fin, is performed to visualize the flow field around the caudal fin. A plate immersed in a water tank is driven to oscillate vertically by its leading edge. A quantitative analysis of the thrust generated by the plate, which is difficult to explore experimentally, is performed over a range of non-dimensional flapping frequencies 0.93 <f*< 1.47 to explore the mechanism of thrust generation in more detail. Comparisons are made between three different flapping frequencies around the structural resonance. Numerical results at different flapping frequencies provide a reasonable estimate of the trailing edge amplitude and phase lag of the motion of the plate’s leading and trailing edges. The pressure distribution and deformation of the plate are analyzed to estimate the time evolution of the maximum and minimum thrust generation during the flapping period. Variations in pressure distribution on the plate surface are mainly due to the displacement of the trailing edge relative to the leading edge. Thrust is mainly provided by the pressure difference at the trailing edge. The maximum thrust was found to correspond to the maximum relative deformation of the trailing edge. The optimum frequency f* = 1.2 corresponding to the maximum thrust generation does not coincide with the structural resonance frequency, but remains at a frequency slightly higher than the resonance. These results indicate that the relative deformation of the plate plays an important role in the estimation of the flow field and the associated thrust generation. The numerical results may provide new guidelines for the design of robotic underwater vehicles.

Power sector decarbonization planning considering renewable resource variability and system operational constraints

Bottom-up long-term planning models generally consider low levels of spatial, temporal, and technical details to reduce associated computation. However, these details are required to capture spatial and temporal variability of Renewable Energy Sources (RESs) and perform harmonized dispatch of conventional generating units. In their absence, models may overestimate RESs uptake and underestimate the quantum of required flexible resources. This may create a false impression of sector decarbonization and the obtained capacity mix may result in frequent RES or load curtailment during real-time system operations. In this context, this study aims to improve upon the shortcomings of conventional planning approaches and develop a TIMES based planning model for the Indian power sector. The model adopts high spatial and temporal definitions of 5 regions and 288 sub-annual timeslices. RESs are categorized into sub-classes based on annual capacity factors to capture their intra-regional variations without further increasing the spatial resolution. Each month is represented by a day of chronological hourly resolution that facilitates the capture of RES temporal variations and incorporation of operational aspects of generating units such as minimum stable generation, ramp limits and partial load operation. The impact of these operational parameters on system planning is analysed to identify a trade-off between planning accuracy and computational complexity. The study is relevant for countries that are rigorously following their decarbonization plans with high penetration of variable RESs and have a similar trajectory as that of India. The results indicate that decarbonization levels can be better assessed if capacity mix and flexible resources are adequately valued by considering operational parameters at the planning stage for a power system dominated by low flexible generation.