Low-cost Generation Research Articles

The Calibrated Safety Constraints Optimal Power Flow for the Operation of Wind-Integrated Power Systems

As the penetration of renewable energy sources (RESs), particularly wind power, continues to rise, the uncertainty in power systems increases. This challenges traditional optimal power flow (OPF) methods. This paper proposes a Calibrated Safety Constraints Optimal Power Flow (CSCOPF) model that uses the Improved Acceleration Coefficient-Based Bee Swarm algorithm (IACBS) in combination with the equivalent current injection (ECI) model. The proposed method addresses key challenges in wind-integrated power systems by ensuring preventive safety scheduling and enabling effective power incident safety analysis (PISA). This improves system reliability and stability. This method incorporates mixed-integer programming, with continuous and discrete variables representing power outputs and control mechanisms. Detailed numerical simulations were conducted on the IEEE 30-bus test system, and the feasibility of the proposed method was further validated on the IEEE 118-bus test system. The results show that the IACBS algorithm outperforms the existing methods in both computational efficiency and robustness. It achieves lower generation costs and faster convergence times. Additionally, the CSCOPF model effectively prevents power grid disruptions during critical incidents, ensuring that wind farms remain operational within predefined safety limits, even in fault scenarios. These findings suggest that the CSCOPF model provides a reliable solution for optimizing power flow in renewable energy-integrated systems, significantly contributing to grid stability and operational safety.

Analysing the impact of diverse factors on electricity generation cost: Insights from Sri Lanka

The primary responsibility of a power system utility is to provide continuous, high-quality electricity at a fair and competitive price. To maintain low generation costs while utilising diverse energy sources, optimisation methodologies are crucial. Water value and generation costs exhibit significant variability on seasonal, daily and timely basis and reflect dynamic interactions between electricity demand and power plant availability. Currently, power system planners often overlook these seasonal and time-of day dependent variations in water value and generation costs. This research paper addresses this gap by analysing how fluctuations in electricity demand and power plant availability affect generation costs in the Sri Lankan power system. It introduces a novel economic dispatch model and presents three methods for estimating water value to calculate seasonal and time-of-day electricity costs. The discussion highlights how these findings can utilise policymaking, particularly in the context of electricity pricing debates and water management for agriculture versus electricity generation, as well as in calculating the water value for each reservoir.

Coordinated energy storage and network expansion planning considering the trustworthiness of demand-side response

The enhancement of economic sustainability and the reduction of greenhouse gas (GHG) emissions are becoming more relevant in power system planning. Thus, renewable energy sources (RESs) have been widely used as clean energy for their lower generation costs and environmentally friendly characteristics. However, the strong random uncertainties from both the demand and generation sides make planning an economic, reliable, and ecological power system more complicated. Thus, this paper considers a variety of resources and technologies and presents a coordinated planning model including energy storage systems (ESSs) and grid network expansion, considering the trustworthiness of demand-side response (DR). First, the size of a single ESS was considered as its size has a close effect on maintenance costs and ultimately affects the total operating cost of the system. Second, it evaluates the influence of the trustworthiness of DR. Third, multiple resources and technologies were included in this high-penetration renewable energy integrated power system, such as ESSs, networks, DR technology, and GHG reduction technology. Finally, this model optimizes the decision variables such as the single size and location of ESSs and the operation parameters such as thermal generation costs, loss load costs, renewable energy curtailment costs, and GHG emission costs. Since the problem scale is very large not only due to the presence of various devices but also both binary and continuous variables considered simultaneously, we reformulate this model by decomposition. Then, we transform it into a master problem (MP) and a dual sub-problem (SP). Finally, the proposed method is applied to a modified IEEE 24-bus test system. The results show computational effectiveness and provide a helpful method in planning low-carbon electricity power systems.

Two-step preparation of methylammonium lead triiodide perovskite film via electrospray deposition of methylammonium iodide solution for solar cell applications

Solution-processable perovskite solar cells (PSCs) have the potential to revolutionize solar cell technology by enabling low power generation costs via low-cost device fabrication. However, most existing research regarding PSCs relies on the spin-coating method, which is not conducive to large-area film deposition. Therefore, the development of an alternative deposition method for perovskite films has become increasingly important for commercialization, for which electrospray deposition is a promising technique. This study investigates the two-step preparation of methylammonium lead triiodide (MAPbI3) perovskite films via the electrospray deposition of a methylammonium iodide (MAI) solution on a spin-coated PbI2 film. The gradual conversion of PbI2 to MAPbI3 with increasing MAI deposition time was revealed, accompanied by an increase in the size of the perovskite crystals. In addition, PSCs were successfully fabricated by electrospraying MAI, achieving a considerable power conversion efficiency of 7.86 % at the optimal MAI deposition time.

GLNAS: Greedy Layer-wise Network Architecture Search for low cost and fast network generation

The process of applying machine learning algorithms to practical problems can be a challenging and tedious task for non-experts. Previous research has sought to alleviate this burden by introducing automated machine learning techniques, including Network Architecture Search (NAS) and Differentiable Architecture Search (DARTS). However, these methods use a fixed number of layers and predefined skip connections which impose limitations on the generation of an optimal network architecture. In this paper, we propose a novel approach called Greedy Layer-wise Network Architecture Search (GLNAS), which trains network layers one after another and evaluates the network’s performance after each layer is added. GLNAS also assesses the effectiveness of skip connections between layers by testing various outputs of previous layers as an input to the current layer. Our experiment results demonstrate that the network generated by GLNAS requires fewer parameters (i.e., 3.5 millions in both CIFAR-10 and CIFAR-100 datasets) and GPU resources during the searching phase (i.e., 0.17 and 0.24 GPU days in CIFAR-10 and CIFAR-100 datasets respectively) than many existing methods.

Glucose Detection Based on Light Reflection in Modulated Optical Fibers for Continuous Diabetes Monitoring

<span lang="EN-US">Diabetes mellitus is a chronic disease characterized by elevated blood glucose levels. Approximately 463 million adults worldwide have diabetes, and nearly half of them remain undiagnosed. Early diagnosis and treatment of diabetes are crucial to prevent serious complications. Continuous glucose monitoring (CGM) offers numerous advantages over traditional fingertip blood glucose measurements. CGM allows patients to track their glucose levels in real time, identify patterns, and adjust their diet and medication appropriately. This research presents a novel optical fiber-based glucose sensor utilizing the macrobending modulation technique. This method offers several advantages, including ease of use, low cost, and strong signal generation. The sensor exploits the refractive index difference between the glucose solution and the optical fiber. Variations in glucose concentration induce changes in the refractive index, which are converted into voltage signals. The sensor exhibits a sensitivity of 337 mV/decade and demonstrates a linear relationship between the voltage signal and glucose concentration within the range of 0-10 mM. The macro bending-modulated optical fiber sensor shows potential as a simple, cost-effective, and efficient CGM tool. Further research is necessary to enhance the sensor's sensitivity and stability and to evaluate its performance in biological samples. </span>

Numerical characterization of capacitively coupled plasma driven by tailored frequency modulated radio frequency source

Capacitively coupled plasma (CCP) is widely used in plasma etching and deposition processes because of its low cost, simple structure, and easy generation of a uniform plasma in large areas. Conventional CCPs are operated under a fixed frequency power source; however, CCPs driven by a variable frequency power source are poorly understood. In this paper, numerical simulations of CCPs driven by frequency modulated (FM) radio frequency (RF) sources within the frequency range of 2 MHz–18 MHz are carried out with a particle-in-cell/Monte Carlo collision model. Our research indicates that the CCP driven by an FM RF source can maintain a stable glow discharge and form a time-dependent plasma. Plasma density, electron and ion current, energy and heating rate, ion flux, and energy on the electrodes fluctuate consistently with the FM period. The electron and ion energy distribution function can also be modulated by the frequency variation of the FM source. A multi-peak structure that varies and shifts with frequency variation is observed in the ion energy distribution function. In addition, by fixing the chirp period while varying the start or end frequency of the chirp signal (start frequency from 0.4 to 6 MHz, or end frequency from 18 to 48 MHz), effective modulations can be produced on the electron density, electron energy, and the shape of the EEPF and IEDF.

Water-Based Generators with Cellulose Acetate: Uncovering the Mechanisms of Power Generation.

Power generation technologies based on water movement and evaporation use water, which covers more than 70% of the Earth's surface and can also generate power from moisture in the air. Studies are conducted to diversify materials to increase power generation performance and validate energy generation mechanisms. In this study, a water-based generator was fabricated by coating cellulose acetate with carbon black. To optimize the generator, Fourier-transform infrared spectroscopy, specific surface area, zeta potential, particle size, and electrical performance analyses were conducted. The developed generator is a cylindrical generator with a diameter of 7.5 mm and length of 20 mm, which can generate a voltage of 0.15 V and current of 82 μA. Additionally, we analyzed the power generation performance using three factors (physical properties, cation effect, and evaporation environment) and proposed an energy generation mechanism. Furthermore, we developed an eco-friendly and low-cost generator using natural fibers with a simple manufacturing process. The proposed generator can contribute to the identification of energy generation mechanisms and is expected to be used as an alternative energy source in the future.

Development of a small wind turbine for stand-alone system in rural environment. Reuse and recycling of electric motors.

This paper studies the feasibility of using small electrical machines (e.g. automotive alternator, induction motors of domestic applications or electrical motors of some industrial application) as low cost generators for small wind turbine or small hydro power; its transformation in generators is not difficult. The objective is to provide a comparison among permanent magnet synchronous generator PMSG with different topologies (rotor configurations). The analysis was performed using FEMM-2D simulation software, which is based on finite element method. Small wind and hydro power systems are very attractive to support the energy demand for rural areas or developing countries where the electrical microgrid infrastructure is limited. Claw-pole automotive alternators can provide low cost alternative to permanent magnet synchronous generators for small wind and hydro turbines applications. The objective is the integration of hybrid energy conversion systems in microgrids and the development of small stand-alone systems in rural environment.

A swarm-intelligent based load-shifting strategy for clean and economic microgrid operation

The required load in a typical microgrid structure fluctuates from hour to hour. Based on the peaks and troughs of the load demand curve, the power system utilities preset different price of electricity at various periods of the same day which is referred to as time-of-use (TOU) pricing policy. An optimal economic strategy called demand side management (DSM) reduces load during peak hours by shifting the elastic loads and compensates the shifted load by increasing the demand during valley hours. This recreates the total demand pattern on the demand price elasticity relation. The novel benefaction of this research suggests a DSM approach based on a hybrid intelligence technique to attain a compromised solution between minimum generation costs and pollutants emitted by DERs of an LV grid-connected microgrid system. Several grid involvement strategies, power market pricing types, and demand response mechanisms are examined in five separate instances for the microgrid system. The outcomes achieved in each example show that the recommended DSM technique may be applied and is appropriate in terms of cost reduction. When 30–40% of customers participated in the DSM curriculum, the generation cost was reduced by 10–13%. Environment constrained economic dispatch provided a superior compromise amongst lowest generation cost and emission for different microgrid load models. Statistical analysis and comparison of the results from previously published literatures validates the superiority of the proposed approach incorporated with DSM policy.

Frequency‐Constrained Expansion Planning in Competitive Market considering Renewable Failures

In modern generation expansion planning of power systems, installing grid‐connected renewable energy systems is preferred than thermal units due to their low generation cost and environmental pollution. However, the expanded power system must have ability to resist against any outages influenced on the frequency response of the system. So, several frequency‐constrained expansion planning models are extracted to provide a reliable infrastructure to manage the frequency behavior. The main distinction of our model with others is considering the failure of grid‐connected renewables in the expansion planning models. Furthermore, due to the lack of information about the uncertainty of malfunctions, a distributionally robust optimization approach is applied to the problem under several ambiguity radiuses. The results of implementing the proposed method on the IEEE RTS96 case show that increasing the penetration of malfunctioned units can lead to more investment on the thermal units to prevent frequency violation under any outage in the system. With increase of the Kullback–Leibler divergence from zero (stochastic) to 3 (robust), the cost of the robust model is increased about 0.02%. The model is designed for the deregulated market to increase the competition of market through maximizing their benefit and line congestion management with local marginal pricing techniques.

Study on Optimization of MFC Electric Generation Parameters based on Box-Behnken Design

MFC is a new energy technology that has emerged in the fields of environmental protection and energy. MFC has achieved the function of clean pollution and electricity generation, maximizing the environmental protection needs of the current shipping industry. However, MFC has the disadvantages of low power generation, unstable operation and high cost, which restrict its engineering application. This article uses single factor analysis and Box- Behnken experimental design to explore the output voltage of MFC under different levels of power generation parameters. Through variance analysis, the optimal power generation process parameters of MFC are determined to improve its power generation performance. The experimental results show that the order of significance of the parameters is temperature >pH> electrode spacing, the interaction between temperature and electrode spacing, pH and electrode spacing is the most significant, but the interaction between temperature and pH is not significant. Box-Behnken experimental model has good regression, and the optimal power generation parameters for MFC output voltage are: temperature of 29.85 °C, pH value of 6.96, and electrode spacing of 2.03 cm. Under this optimal power generation condition, the voltage predicted by the experimental model can reach 529.998 mV, while the voltage obtained by the actual experiment is 531.4 mV, and the error with the model prediction is only 0.26%, the data predicted by the Box Behnken response surface is reliable. The results show that the model can be well applied to the optimization design of MFC generating parameters.

Random pore-network development methodology based on Voronoi and Delaunay tessellations for residual coal under axial stress

Coal spontaneous combustion (CSC) in the gob areas is considered to be an important safety issue in the coal industries. Numerical simulation is a reasonable tool for predicting and preventing this problem. The commonly applied finite-volume and finite-element techniques are computationally expensive when they must account for pore-scale phenomena. A pore-network model (PNM) has the advantage of lower computational cost while also simulating heat and mass transfers in porous media at scale with reasonable accuracy. This study provides a method for extending pore networks to packed coal particles with a wide spectrum of size distributions, and to generate pore networks of arbitrary size within a range. This method was developed based on the Voronoi and Delaunay tessellations theories. Statistical data on the size distribution, porosity, and permeability of packed coal particles were collected experimentally. This method requires a relatively low network generation cost for the preservation of the voids that are formed among larger particles and characterize the effect of fine particles filling in throat channels by reference to a conductivity adjustment factor ηi, which depends on axial stress. The average relative error of predicted and experimental permeability does not exceed 5% when this new pore-network construction procedure is used. The predicted result holds until the volume upscaling ratio reaches 58.

Optimal Electricity Imbalance Pricing for the Emerging Penetration of Renewable and Low-Cost Generators

Problem definition: With the rise of renewables and the decline of fossil fuels, electricity markets are shifting toward a capacity mix in which low-cost generators (LCGs) are dominant. Within this transition, policymakers have been considering whether current market designs are still fundamentally fit for purpose. This research analyses a key aspect: the design of real-time imbalance pricing mechanisms. Currently, markets mostly use either single pricing or dual pricing as their imbalance pricing mechanisms. Single-pricing mechanisms apply identical prices for buying and selling, whereas dual-pricing mechanisms use different prices. The recent harmonization initiative in Europe sets single pricing as the default and dual pricing as the exception. This leaves open the question of when dual pricing is advantageous. We compare the economic efficiency of two dual-pricing mechanisms in current practice with that of a single-pricing design and identify conditions under which dual pricing can be beneficial. We also prove the existence of an optimal pricing mechanism. Methodology/results: We first analytically compare the economic efficiency of single-pricing and dual-pricing mechanisms. Furthermore, we formulate an optimal pricing mechanism that can deter the potential exercise of market power by LCGs. Our analytical results characterize the conditions under which a dual pricing is advantageous over a single pricing. We further compare the economic efficiency of these mechanisms with respect to our proposed optimal mechanism through simulations. We show that the proposed pricing mechanism would be the most efficient in comparison with others and discuss its practicability. Managerial implications: Our analytical comparison reveals market conditions under which each pricing mechanism is a better fit and whether there is a need for a redesign. In particular, our results suggest that existing pricing mechanisms are adequate at low/moderate market shares of LCGs but not for the high levels currently envisaged by policymakers in the transition to decarbonization, where the optimal pricing mechanism will become more attractive.Funding: R. Belo acknowledges funding by Fundação para a Ciência e a Tecnologia [UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab – PINFRA/22209/2016], POR Lisboa, and POR Norte [Social Sciences DataLab, PINFRA/22209/2016].Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2021.0555 .

Generation expansion planning with a renewable energy target and interconnection option: A case study of the Sulawesi region, Indonesia

Sulawesi is a strategic economic region in eastern Indonesia that is facing high growth in electricity demand. Two challenges need to be addressed to achieve its renewable energy (RE) target. The region comprises two unconnected electricity systems, and its RE resources are scattered geographically. It is therefore harnessing RE resources and interconnecting these two electricity systems can be an optimal scenario for generation expansion planning (GEP). This study aims to develop an open-source GEP model for the Sulawesi region as well as identify the optimal electricity development pathway while considering not only the need to achieve higher penetration of renewables and reduce CO2 emissions but also the option and associated benefits and costs of interconnecting the two distinct electricity systems. The results show that the optimal RE development pathway is the interconnection scenario, which ensures a lower generation cost with reduced emissions. This scenario reduces the cost by USD 258.8 million compared with the total cost of the isolated scenario and ensures the RE target of 31% by 2050. This study recommends that investment in hydro and wind energy should be simultaneously encouraged, and robust policies are required to support investments in RE sources, such as geothermal, biomass, and solar energy.

Experimental measurements on the microbubble characteristics and dissolved oxygen (DO) in water using single and twin-Venturi type microbubble generators

The aim of this paper is to develop low cost and low power consumption microbubble generator to improve the mass transfer of gas to liquid. Microbubble aeration used in aquaculture to improve dissolve oxygen level, water recycling through dissolved air flotation (DAF), oil refinement and reduction of skin friction on ship Hull. A single Venturi and 3 twin-Venturis microbubble generators are manufactured and tested in this study. Experimental data on microbubbles diameters distribution and dissolved oxygen are presented. The main conclusions are: i) the mean microbubbles diameters produced by twin-Venturi are smaller by 10 µm than single Venturi generator; ii) the dissolved oxygen concentration was higher for twin-Venturi microbubble generator; iii) the microbubbles size distribution from twin-Venturis have a narrower distribution which reduces the probability of bubbles coalesce as they have very close values of velocities; iv) the bubbles diameters and velocities increase with the height in the water tank.

A short-term forecasting of wind power outputs using the enhanced wavelet transform and arimax techniques

South Korea has announced a plan to increase the proportion of renewable energy generation to 20% and reduce traditional energy generation by 2030. Among renewable energy resources, wind power has the advantage of relatively low power generation costs. However, it is difficult to forecast, as the output varies significantly depending on changing wind conditions such as the temperature, wind speed, and wind direction. We believe that short-term wind energy forecasts are the most important part for coping with these fluctuations and minimizing scheduling errors, thereby making the grid more reliable and reducing market service costs. Accordingly, we proposed a practical short-term wind power output forecasting method using a novel ensemble model based on a wavelet transform and autoregressive integrated moving average with explanatory variable (ARIMAX) approach. To demonstrate that the model has a good forecasting performance, we applied historical wind speed and wind power output data obtained from Jeju Island's wind farm to the model, and compared them with forecasted values. The normalized mean absolute error (NMAE) was used as the error metric. The comparison results were described for three supervisory control and data acquisition points. The average NMAE was approximately 3%. In addition, an N-1 contingency analysis was conducted to check the voltage profiles and flow limits in the context of a real power system, to ensure that the power system operated stably even with the forecasted values. The system worked successfully with the forecasted values, and can be deployed as application software for energy management systems in South Korea.

Electricity Tariff Design: A Survey

In a perfectly competitive market, electricity is priced at the Marginal Cost (MC); MC pricing guarantees economic efficiency (Gunatilake, et al. 2008). In other words, efficient electricity tariffs consider all power supply costs. To a great degree, it also accounts for capital investments for future expansion and up-gradation (Kojima, et al. 2014). In a free market, market forces of demand and supply pushed for MC recovery. In contrast, for a regulated market, the regulator sets the tariff according to the costs and reasonable return determined through the regulatory process. The regulator followed pre-determined guidelines, parameters, and standards set by the government; it may or may not be MC pricing. When a regulated tariff is set at a low level, it distorts the development/ functioning of the market at both the wholesale and retail levels. “If regulated end-user prices are not in line with wholesale market conditions, suppliers without significant low-cost generation capacity or equivalent long-term contracts will not be able to make competitive offers that will allow them to recover their costs. Consequently, with a limited number of suppliers, there will be no development of the wholesale markets. Liquidity will remain at a low level. As a result, neither the wholesale nor retail markets will be competitive” (Cited from Suzzoni, 2009, p. 5).

Melamine-Based Hydrogen-bonded Systems as Organoelectrocatalysts for Water Oxidation Reaction.

Applications of small organic molecules and hydrogen-bonded aggregates, instead of traditional transition-metal-based electrocatalysts, are gaining momentum for addressing the issue of low-cost generation of H2 to power a sustainable environment. Such systems offer the possibility to integrate desired functional moieties with predictive structural repetition for modulating their properties. Despite these advantages, hydrogen-bonded organic systems have largely remained unexplored, especially as electrocatalysts. Melamine and adipic acid-based hydrogen-bonded organic ionic (BMA) and co-crystal systems developed under varying temperatures are explored as electrocatalysts for water oxidation reaction (WOR). These systems are easily modifiable with precisely designed molecular architecture and judiciously positioned nitrogen atoms. Combined effect of charge-assisted hydrogen bonding stabilizes the ionic BMA system under corrosive alkaline conditions and augments its remarkable electrocatalytic WOR activity, achieving a current density of 10 mA cm-2 at an overpotential of 387 mV and Faradaic efficiency ∼94.5 %. The enhanced electrocatalytic ability of BMA is attributed to its hydrophilic nature, unique molecular composition with complementary hydrogen-bonded motifs and a high density of positively charged nitrogen atoms on the surface, that facilitates electrostatic interactions and accelerate charge and mass transport processes culminating in a turnover frequency of ∼0.024 s-1 . This work validates the potential of hydrogen-bonded molecular organo-electrocatalysts towards WOR.

Distribution locational pricing mechanisms for flexible interconnected distribution system with variable renewable energy generation

Nowadays, distribution locational pricing mechanism has been widely used in the radial distribution network to guide the energy consumption and promote the renewables utilization. Aiming to explore the reasonable pricing policy which is applicable to the merging flexible interconnected distribution system (FIDS), this paper develops two different distribution locational pricing mechanisms for distribution lines interconnected by soft open points (SOPs). First, based on the Wasserstein ambiguity sets for uncertainties from the main grid and distribution network, a carbon-oriented distributionally robust economic dispatch model is constructed for FIDS considering different price and carbon signals from the main grid. Then, by leveraging the optimal scheme from economic scheduling model, distribution locational marginal prices (DLMPs) and equivalent DLMPs (EDLMPs) are presented to measure the marginal cost and actual cost for energy consumption in the FIDS respectively. The calculation and decomposition methods of these price signals are also developed. In case studies, a practical 63-node FIDS is chosen to verify the effectiveness of the proposed methods. Numerical results illustrate the characteristics of DLMPs and EDLMPs in FIDS under multiple uncertainties. Comparing to DLMPs, EDLMPs are more appropriate to FIDS because this pricing mechanism can reflect the lower generation cost of renewables for each consumer.