Upper Level Research Articles

Financial arbitrage in electricity markets via virtual bidding

The concept of virtual bidding serves as a pure financial tool in electricity markets, aiming at enhancing their performance. Although virtual bidding helps reduce price gaps between different trading floors, there is evidence suggesting that this does not necessarily lead to improved welfare for market consumers. To gain a deeper understanding of virtual bidding and its impact on electricity market prices, this work delves into the strategic behavior of a financial player engaged in an electricity pool-based market. To this end, a bi-level model is formulated. The upper level optimizes the expected revenues of the virtual bidder while the lower-level represents the clearing of the market under network-constrained economic dispatch through a two-stage stochastic programming. The proposed model derives optimal arbitrage strategies in both scenarios of explicit and implicit virtual bidding. It also assesses the performance of virtual bidding under stochastic generation and transmission contingencies, including considerations of up-to-congestion virtual bidding.

Intra-site spatial approaches based on taphonomic analyses to characterize assemblage formation at Pleistocene sites: a case study from Buena Pinta Cave (Pinilla del Valle, Madrid, Spain)

Buena Pinta Cave (Pinilla del Valle, Madrid) has been interpreted as a hyena den with sporadic occupations of Homo neanderthalensis in the western part of the site (level 23). In order to identify the different formation processes in this area of the site, spatial analyses have been carried out with GIS and spatial statistics based on the taphonomic analysis of the faunal remains. Based on the vertical and sectional analyses of the assemblage, it has been possible to determine that level 23 actually corresponds to three archaeological levels with well-differentiated characteristics: a lower level with few faunal remains and fossil-diagenetic alterations related to humid environments associated with clays; an intermediate level with a high percentage of remains with water-related modifications and evidences of transport; and an upper level delimited mainly thanks to by a paraconformity evidenced by the concentration of weathered remains in this area and a significant reduction in remains with water-related alterations above. The results obtained show the necessity to redefine field layers and the usefulness of integrating taphonomic data and spatial studies.

BilevelJuMP.jl: Modeling and Solving Bilevel Optimization Problems in Julia

In this paper, we present BilevelJuMP.jl, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Because of the generality and flexibility that our library inherits from JuMP’s syntax, our package allows users to model bilevel optimization problems with conic constraints in the lower level and all constraints supported by JuMP in the upper level including conic, quadratic, and nonlinear constraints. Moreover, the models defined with the syntax from BilevelJuMP.jl can be solved by multiple techniques that are based on reformulations as mathematical programs with equilibrium constraints (MPEC). Manipulations on the original problem data are possible due to MathOptInterface.jl’s structures and Dualization.jl features. Hence, the proposed package allows quick modeling, deployment, and thereby experimenting with bilevel models based on off-the-shelf mixed-integer linear programming and nonlinear solvers. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Funding: The authors were partially supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. The work of A. Street was also partially supported by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). The work was partially funded by the project P&D ANEEL PD-00403-0050/2020 sponsored by ENGIE BRASIL ENERGIA S.A. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0135 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0135 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Bi-level planning approach for incorporating the demand-side flexibility of cloud data centers under electricity-carbon markets

With the prevalence of cloud computing applications, cloud data centers (CDCs) are proliferating around the world. However, in the context of hybrid energy‑carbon markets environment, the high energy costs and environmental expenses caused by CDC operation are pressing CDC owners to restructure the future development of CDC in a more economical and low-carbon manner. The potential spatio-temporal transferability and reducibility of workloads provides CDCs with significant flexibility in their operations and thus may interact with the power grid as active demand users. Nonetheless, other than private data centers, public CDCs have no direct control over the workloads submitted by terminal cloud users. As such, this paper presents a bi-level model for CDC allocation planning, so as to incorporate cloud service-demand response (CS-DR) from the perspective of a hybrid electricity-carbon market. The upper level pertains to multi-domain resource collaborative planning model, which determines the optimum siting and sizing of CDCs as well as the incentive design for CS-DR program, with the objective of maximizing the total expected benefits of CDC. The lower level models correspond to the market clearing (electricity-carbon tariff model) of Independent system operator (ISO) and the decision-making of cloud users regarding CS-DR participation. The proposed model belongs to a bi-level mixed integer nonlinear programming problem with two non-convex lower levels, which can be intractable in mathematics. To solve such difficult problem, a hybrid solution method combining multiple linearization techniques and reformulation and decomposition (R&D) strategy based on column-and-constraint generation (C&CG) algorithm is developed. The proposed model is demonstrated on a modified IEEE 30-bus test case, and the simulation results verified the effectiveness of the proposed approach.

Sustainable road network design considering hydrogen fuel cell vehicles

Environmental pollution and energy shortages have brought about an increased focus on new energy vehicles. Hydrogen fuel cell vehicles (HFCVs) have experienced rapid development due to the potential to alleviate energy pressures and reduce pollution emissions. Near zero-carbon emissions offer a promising avenue for promoting sustainable transportation development. To evaluate the impact of HFCVs on the transportation environment, this paper investigates the problem of sustainable transportation network design including HFCVs. Specifically, the problem is formulated as a bi-level multi-objective programming problem, with the upper level aimed at determining the optimal network design scheme considering multiple objectives, while the lower level addresses the mixed traffic flow that comprises both HFCVs and fuel vehicles. To solve the multi-objective sustainable network design problem, an integrated solution framework that combines the particle swarm optimization (PSO) algorithm with the Frank-Wolfe algorithm (FW) is developed. Specifically, the PSO algorithm is utilized to solve the upper-level model and identify the optimal network design schemes, while FW algorithm is adopted to handle mixed traffic flow assignments. Finally, the proposed model and algorithm are implemented in two numerical experiment to demonstrate their effectiveness and efficiency.

A Bi-level optimization strategy for electric vehicle retailers based on robust pricing and hybrid demand response

The high penetration of electric vehicles (EVs) poses both opportunities and challenges for power systems. EV retailers, playing a critical role in the demand response mechanism, face market risks caused by uncertainties in electricity consumption and prices. To address the operational issues of large-scale EVs and tap the potential of EV retailers, a temporal and spatial domain-based optimization strategy is proposed, which is implemented on bi-level (referring to transmission and distribution grid networks). First, a physical scheduling model of the grid is established, consisting of a novel hybrid demand response mechanism considering the incentives of EV retailers and the retail electricity price of EV users, and a new robust retail electricity pricing strategy handling the uncertainties of EV behavior and the electric market. Then, a bi-level optimization strategy is presented: at the upper level, in the transmission network, based on the robust pricing strategy, a unit commitment model that coordinates the hybrid demand response with other distributed energy resources is designed to optimize load periods of EVs in the time domain; at the lower level, in the distribution network, an optimal power flow model is proposed to spatially dispatch the location of EV loads. The impacts of retail price profile, EV penetration, hybrid demand response mechanism, and EV load location are analyzed in ten tests using the IEEE 33 distribution network. Simulation results indicate that the robust pricing strategy can effectively handle uncertainties, the integration of the hybrid demand response mechanism into scheduling can ensure the benefits of all participants, and the bi-level optimization strategy can accommodate distributed energy resources temporally and spatially.

A multiscale approach to statistical downscaling of daily precipitation: Israel as a test case

AbstractRainfall in the Eastern Mediterranean is strongly modulated by complex topography and localized mesoscale processes. General circulation models (GCMs) struggle to capture daily precipitation variability in the region, both in time and in space. Rain in the Eastern Mediterranean occurs within a hierarchy of scales, as synoptic scale structures often drive local rainfall patterns. Daily rain prediction in the region can therefore benefit from analog downscaling—a nonlinear regression of a high‐resolution predictand from past synoptic‐scale predictors. We present a multiscaled downscaling algorithm of daily rain over Israel. The underlying goal is to create a mechanism‐based tool that will improve the analysis and prediction of precipitation on short time scales in models that cannot produce the field explicitly. We train the algorithm using coarse grid ERA5 reanalysis data and measurements from 21 rain gauges. The routine uses a k‐nearest neighbours algorithm to find the most similar past instances (i.e., analogs) for every predicted day. Analog selection is performed in two steps, based on scale (synoptic and local), as to not overshadow correlative but local predictors. The algorithm also includes several unique aspects tailored to Mediterranean climate: subdaily predictors of cyclone life cycles; representation of upper level cyclonic drivers; and the inclusion of rainfall potential using the Modified K‐Index (MKI). The proposed algorithm has better accuracy (66% correct predictions) compared to non‐downscaled reanalysis and climatological predictions. It better captures the spatial rainfall variance, mitigates the “drizzle bias,” and improves skill in extreme event prediction. However, it underestimates very rainy events and has trouble fully representing the spatial variance in the region. Nonetheless, our algorithm represents the potential for computationally inexpensive downscaling of daily precipitation in the Mediterranean with various possible applications, for example, characterization of droughts and storms, linking hydrological and synoptic scale processes and introducing uncertainty estimates using large ensembles.

Risk assessment of nutrients: There must be a threshold for their effects

Nutrients serve physiological functions in a dose-dependent manner and that needs to be recognized in risk assessment. An example of the consequences of not properly considering this can be seen in a recent assessment by the European Food Safety Authority (EFSA). EFSA concluded in 2022 that the intake of added and free sugars should be “as low as possible in the context of a nutritionally adequate diet”. That conclusion of EFSA is based on the effects on two surrogate endpoints for an adverse effect found in randomized controlled trials with high sugars intake levels: fasting glucose and fasting triglycerides. The lowest intake levels in these trials were around 10 energy% and at this intake level there were no adverse effects on the two outcomes. This indicates that the adverse effects of sugars have an observable threshold value for these two endpoints. The most appropriate interpretation from the vast amount of data is that currently no definitive conclusion can be drawn on the tolerable upper intake level for dietary sugars. Therefore, EFSA's own guidance would lead to the conclusion that the available data do not allow the setting of an upper limit for added sugars and hence, that more robust data are required to identify the threshold value for intake of sugars.

Multilevel Laminoplasty for CSM: Is C3 Laminectomy Better Than C3 Laminoplasty at the Superior Vertebra?

In a multilevel cervical laminoplasty operation for patients with cervical spondylotic myelopathy (CSM), a partial or complete C3 laminectomy may be performed at the upper level instead of a C3 plated laminoplasty. It is unknown whether C3 technique above the laminoplasty affects loss of cervical lordosis or range of motion. Patients undergoing multilevel laminoplasty of the cervical spine (C3-C6/C7) at a single institution were retrospectively reviewed. Patients were divided into two cohorts based on surgical technique at C3: C3-C6/C7 plated laminoplasty ("C3 laminoplasty only", N = 61), C3 partial or complete laminectomy, plus C4-C6/C7 plated laminoplasty (N = 39). All patients had at least 1-year postoperative X-ray treatment. Of 100 total patients, C3 laminoplasty and C3 laminectomy were equivalent in all demographic data, except for age (66.4 vs. 59.4 years, p = 0.012). None of the preoperative radiographic parameters differed between the C3 laminoplasty and C3 laminectomy cohorts: cervical lordosis (13.1° vs. 11.1°, p = 0.259), T1 slope (32.9° vs. 29.2°, p = 0.072), T1 slope-cervical lordosis (19.8° vs. 18.6°, p = 0.485), or cervical sagittal vertical axis (3.1 cm vs. 2.7 cm, p = 0.193). None of the postoperative radiographic parameters differed between the C3 laminoplasty and C3 laminectomy cohorts: cervical lordosis (9.4° vs. 11.2°, p = 0.369), T1 slope-cervical lordosis (21.7° vs. 18.1°, p = 0.126), to cervical sagittal vertical axis (3.3 cm vs. 3.6 cm, p = 0.479). In the total cohort, 31% had loss of cervical lordosis >5°. Loss of lordosis reached 5-10° (mild change) in 13% of patients and >10° (moderate change) in 18% of patients. C3 laminoplasty and C3 laminectomy cohorts did not differ with respect to no change (<5°: 65.6% vs. 74.3%, respectively), mild change (5-10°: 14.8% vs. 10.3%), and moderate change (>10°: 19.7% vs. 15.4%) in cervical lordosis, p = 0.644. When controlling for age, ordinal regression showed that surgical technique at C3 did not increase the odds of postoperative loss of cervical lordosis. C3 laminectomy versus C3 laminoplasty did not differ in the postoperative range of motion on cervical flexion-extension X-rays (23.9° vs. 21.7°, p = 0.451, N = 91). There was no difference in postoperative loss of cervical lordosis or postoperative range of motion in patients who underwent either C3-C6/C7 plated laminoplasty or C3 laminectomy plus C4-C6/C7 plated laminoplasty.

Growth and efficient laser emission of Er3+ doped LGGG single crystal at 2.8 μm

A novel kind of high-quality Er3+:LGGG crystal has been grown using the Czochralski method and exhibited excellent lasing performance for the first time at around 2818 nm in the mid-infrared spectral region. The J-O intensity parameters, spontaneous emission probability, branching ratio, and exited state lifetimes parameters have been calculated for the first time using the J-O theory, providing theoretical references for future analysis of the absorption and emission characteristics of Er3+:LGGG crystals. The fluorescence lifetimes of the upper (4I11/2) and lower (4I13/2) laser levels are 1.42 and 5.18 ms, respectively. Under 976 nm laser pumping, a continuous-wave laser output of 374 mW with excellent beam quality factors Mx2/My2 of 1.374/1.228 has been achieved by using the Er3+:LGGG crystal. These results indicate that Er3+:LGGG crystals are promising materials for generating 2.8 μm mid-infrared lasers.

A Bi-Level Programming Approach to Optimize Ship Fouling Cleaning

Ship fouling has significant adverse effects on vessel performance and environmental sustainability. Therefore, this research study develops a bi-level programming model to simultaneously optimize cleaning equipment deployment by cleaning service providers in the upper level and cleaning decisions by shipping companies in the lower level. To address the interaction within the bi-level problem, the model is transformed into a single-level formulation using the big-M method. This transformation greatly simplifies the complexity of the computation and reduces computation time. Numerical experiments are conducted using real-world data to evaluate the performance of the proposed models. In addition, sensitivity analyses are performed to investigate the influence of key parameters. The results indicate that cleaning service providers primarily purchase equipment in the first year based on the demand distribution. To maximize profit, they may choose to forgo a portion of the demand. The sensitivity analysis reveals that sacrificing part of the demand can lead to an additional USD 27 million in profits compared with satisfying all demand. Moreover, increasing the cleaning price reduces both demand and equipment purchases but increases total profits. Conversely, increasing purchase costs reduces profits and the total amount of equipment purchased. When service providers can no longer generate profits, they are likely to exit the market. These findings offer valuable insights for service providers and shipping companies in the practical deployment of cleaning equipment and foul cleaning decisions, respectively.

Robust Optimal Scheduling of Microgrid with Electric Vehicles Based on Stackelberg Game

With increasing penetration of distributed generators (DG), the uncertainty and intermittence of renewable energy has brought new challenges to the economic dispatch and promotion of environment sustainability of microgrids. Active loads, especially in electric vehicles (EVs), are thought to be an efficient way to deal with the uncertainty and intermittence of renewable energy. One of the most important features of EVs is that their demand will vary in response to the electricity price. How to determine the real-time charging price to guide the orderly charging of EVs and operate with an uncertain renewable energy output represents an important topic for the microgrid operator (MGO). To this end, this paper formulates the optimal pricing and robust dispatch problem of the MGO as a Stackelberg game, in which the upper level minimizes the MGO’s cost, while the lower level minimizes the charging cost of each EV. In the problem, the approximate linear relationship between the node voltage and equivalent load is modeled, and the approximate linear expression of the node voltage security constraint is derived. Using dual optimization theory, the robust optimal dispatch model is transformed into a linear programming model without uncertain variables. Then, the Stackelberg game model is transformed into a mixed integer linear program by using the duality theorem of linear programming. Finally, the effectiveness of the proposed method is proved by simulation within the modified IEEE33-bus system.

A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy

Under the policy of renewable portfolio standard (RPS), many microgrid (MG) users with high electricity consumption are installed with renewable energy (RE) generation devices to complete their RE consumption responsibility and reduce carbon emissions. In view of the conflict between the goals of microgrid operators (MGO) and MG users, it is a challenge to achieve economic optimization for both MGO and MG users at the same time when they participate in system dispatch and complete RE consumption responsibility. Therefore, this paper proposes a bi-level noncooperative dispatch strategy that takes into account user satisfaction and RE consumption willingness. In this bi-level model, the upper level is led by an MGO who decides electricity retail prices, while the lower level is followed by MG users who participate in demand response (DR) and change electricity purchase strategies. First, a novel comprehensive evaluation model is formulated to evaluate users' willingness to consume green electricity. Based on this, users' consumption behavior of green and thermal electricity is modeled independently not only in electricity trading but also in power dispatching. Second, optimization objectives are established with the goal of maximizing MG users' welfare, including user satisfaction improvement and energy purchase cost reduction, as well as maximizing the revenue of the MGO. Then, a Stackelberg game model is constructed, and a differential evolution algorithm nested CPLEX is used to solve the Stackelberg game problem of balancing the interests of both parties. Finally, our simulation analysis shows that under the dispatch strategy in this paper, load peak-valley difference is reduced. In addition, when the green electricity generated within the system is sufficient, based on a high level of users' willingness to consume green electricity, the total consumption of green electricity is increased by 29.5% and the overall welfare of users is increased by 0.75%.

The concept, essence and role of student project activities and project management office placement in the structure of its management

The article studies peculiarities of project activity organization in educational organizations of higher education. The relevance of the study is determined by higher education organizations’ interest in introducing and developing project activity and using concepts related to it. The concept of project is used by higher education organizations not in its direct meaning, but to reflect students’ practical activity. The article describes peculiarities of university-based project office functioning and their tasks. Justifications for involving third-party organizations such as outsourcing to implement functions of the upper management level of project management office have been given. The authors resort to scientific literature and other official sources that confirm correctness and validity of their arguments.

Complex neuroimaging study of the proximal segment after rigid fixation and dynamic stabilization in patients with degenerative lumbar disease

Background. The development of the adjacent level syndrome and, as a consequence, adjacent segment degenerative disease are currently the most common complications of decompression and stabilization surgery with the development of segmental instability. The aim of the study. To conduct a comprehensive neuroimaging assessment of  the proximal adjacent segment after rigid fixation and dynamic stabilization in degenerative lumbar disease. Materials and methods. We conducted a prospective multicenter study of the results of surgical treatment of 274 patients with degenerative-dystrophic diseases of the lumbar spine, who underwent monosegmental decompression and stabilization surgery using the TLIF (transforaminal lumbar interbody fusion) technique and open transpedicular rigid fixation, as well as open hemilaminectomy with stabilization of the operated segments with nitinol rods. The study included radiography, diffusion-weighted magnetic resonance imaging and computed tomography (dualenergy mode) of intervertebral discs and isolated facet degeneration of the upper adjacent level. Results and discussion. Combination of the initial proximal segment degeneration in the form of  facet joints degeneration (density of cartilaginous plate  – 163.5 ± 14.2 HU, density of external facet – 709.35 ± 13.6 HU, density of internal facet – 578.1  ±  12.1  HU), Pfirrmann III, IV  grade degeneration of intervertebral disc and a measured diffusion coefficient of less than 1300 mm2/s cause high risks of developing adjacent segment degenerative disease, which regulates the use of monosegmental dynamic fixation with nitinol rods, or preventive rigid fixation of the adjacent segment. Conclusion. Using complex neuroimaging in the preoperative period makes it possible to predict the results of surgical treatment, take timely measures to prevent degenerative diseases of the adjacent segment, and to carry out dynamic monitoring of processes in the structures of the spinal motion segment.

α-Lipoic acid as an ingredient of specialized food product and dietary supplement

A review of the literature in recent years was carried out using the RSCI, Google Scholar, Pubmed, and ResearchGate databases.The purpose of the review was to assess the content of α-lipoic acid (ALA) in foods and compare the doses allowed for use in dietary supplements and specialized food products with doses that provide a clinical effect. ALA or thioctic acid is synthesized in the organism and is also found in foods in free oxidized and reduced form, bound to proteins by hydrogen bonds, as well as covalently bound to lysine residues (lipoyl-lysine) in proteins, which complicates the analytical determination and reduces the bioavailability of this vitamin-like substances. Various methods for determining the natural content of individual forms (ALA and lipoyl-lysine) and their total content in food products have been described. The content of free ALA in 100 g of raw products of animal origin varies from 0.22 to 1.35 mg, of plant origin – from 0.22 to 2.04 mg. Losses during heat treatment reach 77–92%. Lipoyl–lysine content ranged from 2.11–3.99 µg/g heart, 0.56–1.17 µg/g liver, 0.71–1.40 µg/g kidney, while ALA amounts ranged from 0.22 up to 0.55 µg/g heart, from 0.38 to 0.51 µg/g liver. It is difficult to estimate the dietary intake of the total amount of all forms of ALA due to differences in extraction and detection methods. According to the domestic regulatory framework, the adequate level of ALA consumption for adults is 30 mg/day, the upper permissible level of daily consumption for adults as part of specialized food products (SFP), preventive and therapeutic nutrition and dietary supplements is 100 mg/day. ALA is often included in multicomponent dietary supplements and SPP in doses from 15 mg to 100 mg. A positive effect when taken for 10 or more weeks on lipid and carbohydrate metabolism, as well as other clinical effects in patients, is observed when taking ≥ 600 mg of ALA per day, which is significantly higher than the doses allowed for inclusion in the SFP.

Influences of intraseasonal oscillations on a compound cold and wet event in southern China during the Spring Festival travel rush

AbstractIn January 2023 during the Spring Festival travel rush, a compound cold and wet event (CCWE) hit southern China, causing heavy precipitation followed by two cold wave processes. Through an analysis from the intraseasonal oscillation (ISO) perspective, it was found that the cold event is caused by two consecutive cold events, in which upper level midlatitude ISO wave train propagating across the Eurasia favours the formation of blocking high, leading to the expansion of Siberian High and intensification of East Asian winter monsoon. As a result, strong cold advection appeared in the northern boundary of southern China and caused the cooling process. As for the wet event, it was found that a cyclonic ISO anomaly from South China Sea conveyed abundant moisture through the western and southern boundaries and caused the precipitation. It was revealed in the partial lateral forcing (PLF) experiment that the midlatitude ISO signal from the northern boundary caused minimum 2 m temperature to drop by 1.84°C, mainly affecting the northern part of the research area. The tropical ISO from the western and southern boundaries resulted in heavy precipitation for over 40 mm in a belt‐shaped area in 3 days. The combination of the ISOs is the key factor behind this CCWE and our study provides intuitive evidences for this, which is helpful in understanding the mechanisms and providing empirical precursory signals for the forecast of CCWEs.

Mid‐level dry air intrusions over the southern Maritime Continent

AbstractPatterns in extreme precipitation across the Maritime Continent in southeast Asia are known to be modulated by many processes, from large‐scale modes of variability such as the Madden–Julian oscillation, to finer‐scale mechanisms such as the diurnal cycle. Transient mid‐level dry air intrusions are an example of a feature not extensively studied over the Maritime Continent, which has the potential to influence rainfall patterns. Here, we show that these dry air intrusions originate from upper level disturbances along the subtropical jet. Mid‐level cyclonic circulation anomalies northwest of Australia from December to February (DJF) intensify westerlies in the southern Maritime Continent, advecting dry air eastward. In contrast, mid‐level anticyclonic circulation anomalies northwest of Australia from June to August (JJA) intensify southern Maritime Continent easterlies, advecting dry air westward. The resultant transport direction of associated air parcels is also dependent on the seasonal low‐level monsoon circulation. Dry air intrusions are important in influencing low‐level wind and rainfall patterns, suppressing rainfall over seas near the southern Maritime Continent in both seasons, as well as over southern Maritime Continent islands in DJF and the Indian Ocean in JJA. In both seasons there is enhanced rainfall to the east of the intrusion, where there is moist return flow to the extratropics. This study highlights the importance of synoptic‐scale extratropical features in influencing meteorological patterns in the Tropics.

Sizing and energy management of standalone hybrid renewable energy systems based on economic predictive control

This paper aims to design and run a standalone hybrid renewable energy System (HRES) feeding residential building load. The suggested HRES encompasses photovoltaic panels and wind turbines as energy sources, combined with a hydrogen subsystem and a bank of batteries for energy storage. The meteorological input data includes irradiance, temperature, and wind speed for four seasonal weeks. These data sets are collected for a rural site situated in the town of Ras Munif, northern Jordan. The load profiles characterize a selected benchmark residential building. Consequently, a bi-level mixed integer nonlinear programming (BMINLP) problem is formulated to incorporate the designing problem with the energy management process. The upper level represents the sizing problem, while the lower level problem denotes the energy management strategy (EMS). Each problem has its independent objective function, constraints, and optimization variables. The EMS is an economic-based single objective optimization problem expressed as a mixed integer linear programming (MILP) problem. On the contrary, a mixed integer nonlinear programming (MINLP) approach frames the sizing problem to optimize a techno-economic-based multi-objective function. The interaction between the two problems is that the lower problem is an embedded constraint of the upper problem. Moreover, the candidate solutions from the upper problem are treated as fixed parameters in the lower problem. A multi-objective genetic algorithm is used to execute the overall problem by the MATLAB toolbox. The technical and economic performance parameters, including the investment cost, maintenance, operating costs, and others, are assessed based on the best findings. The key finding demonstrates that the summer week has the lowest total cost and energy loss factor, with around 132,000 $ and 0, respectively. Furthermore, the findings reveal that the entire system's energy loss factor for each sample period is less than 0.0009. This value is substantially less than the permitted limit of 0.01.

EV Hosting Capacity Enhancement in a Community Microgrid Through Dynamic Price Optimization-Based Demand Response.

Community microgrids, as an emerging technology, offer resiliency in operation for smart grids. Microgrids are seeing an increased penetration of eco-friendly electric vehicles (EVs) in recent years. However, the uncontrolled charging of EVs can easily overwhelm such electric networks. In this work, we propose an efficient demand response (DR) scheme based on dynamic pricing to enhance the capacity of the microgrid to securely host a large number of EVs. A hierarchical two-level optimization framework is introduced to realize the DR scheme. At the upper level, the dynamic prices for the participating users in DR are optimized while at the lower level, each user optimizes its energy consumption based on the price signal from the upper level. An evolutionary algorithm and a mixed-integer linear programming model is employed to solve the upper and lower level problems, respectively. Energy scheduling problems of the users are solved in a distributed manner which adds to the scalability of the approach. The proposed DR scheme is tested on a microgrid system adopted from the IEEE European low-voltage distribution network. Numerical experiments confirm the effectiveness of the proposed DR scheme compared to the benchmark pricing policies from the literature.