Low-level Model Research Articles

Allocating the capacity of shared energy storage for wind farm groups based on the over-limit power export risk

Energy storage in wind farms can stabilize the fluctuation of wind power output. Shared energy storage can reduce the construction cost of energy storage devices and stimulate the enthusiasm of wind farms to invest in energy storage. The wind power base is composed of multiple wind farm groups. Existing research methods did not consider how to allocate shared energy storage among wind farm groups in the wind power base. This paper proposes an energy storage capacity allocation method for wind farm groups. Firstly, a bilevel model for the shared energy storage allocation is established. The upper-level model optimizes the shared energy storage allocation of each wind farm group with the goal of minimizing the over-limit power export risk in the wind power base; The lower-level model calculates the over-limit power export of each wind farm group according to the energy storage capacity allocation and transfers the value of over-limit power export to the upper-level model. The bilevel model can be converted to a two-stage model that can be solved sequentially; The wind power base in Belgium is used for numerical simulation to verify the effectiveness of the proposed model. Finally, the sensitivity of confidence level, total energy storage capacity, and risk preference factor are analyzed.

Multi-objective optimal dispatching of demand response-enabled microgrid considering uncertainty of renewable energy generations based on two-level iterative strategy

In this study, multi-objective optimal dispatching of demand response-enabled microgrid considering uncertainty in renewable energy generations is designed to obtain optimal energy point sets of microgrid. The proposed dispatching model contains upper-level model and lower-level model. The economic and environmental benefits of the microgrid are adopted as the optimization objectives in the upper-level model and the economic benefits under incentive-based demand response is taken as the optimization objective in the lower-level load demand. In the upper-level model, sequence operation theory is designed to deal with the uncertainty in renewable energy generations, and virtual real-time tariffs and electricity credibility of power consumption are utilized to make demand response by shifting load in the lower-level model. To optimally solve the proposed model, improved enhanced multi-objective optimization sparrow search algorithm (EMOSSA) based on sinusoidal search strategy, diversity variant processing by Cauchy variation and external archive updating mechanism is developed to optimize the objective functions of the upper-level model and mixed integer linear programming CPLEX is employed to determine the load demand for the lower-level model. After that, the power demand plan of the lower-level model and the real-time prices of the upper-level model are updated iteratively to obtain the optimal dispatching solutions using the real-time pricing mechanism. Eventually, experimental results of several operation scenarios illustrate the proposed optimal dispatching method can deal with the uncertainty of renewable energy generations and the randomness of load, thus, achieving a well supply and demand balance between microgrid and users.

Derivation of benchmark doses for male reproductive toxicity in a subacute low-level Pb exposure model in rats

The objectives of the study were to simulate low-level Pb exposure scenario in an animal model and to examine reproductive adverse effects. Based on obtained data, we have performed Benchmark dose (BMD)-response modelling. Male Wistar rats were randomized in seven groups (n = 6): one control and six treated with: 0.1, 0.5, 1, 3, 7, and 15 mg Pb/kg body weight, daily for 28 days by oral gavage. The rats were sacrificed and the blood and testes were used for further analysis of testosterone levels in serum, testicular essential metal levels and histological analysis. The Pb treatment led to a dose-dependent decrease of serum testosterone levels with a negative trend (BMDI 0.17–6.13 mg Pb/kg). Increase of Zn (dose-dependent, BMDI 0.004–19.7 mg Pb/kg) and Cu and a decrease of Mn testicular levels were also detected with unscathed histology of the testes. The presented results might be used in further evaluation of the point of departure in human health risk assessment for Pb.

Network-aware energy management for microgrids in distribution market: A leader-followers approach

With the increasing penetration of distributed energy resources (DERs) into distribution systems, microgrids can participate in the market clearing of distribution-level electricity market. This paper proposes a leader-followers-type bi-level model for energy management and market clearing of distribution system with microgrids based on Stackelberg game. Distribution system operator (DSO) is considered as the leader, and microgrid operators (MOs) as followers. In the proposed model, market clearing problem of distribution system is modeled in the upper level, while the energy management problem of microgrids is modeled in the lower level. The distribution locational marginal price (DLMP) is obtained in the upper level model and then transmitted to the lower level model as price signals for microgrids. The model is then reformulated as a Mathematical Program with Equilibrium Constraints (MPEC) problem and the stochastic MPEC model is constructed with the uncertainty of PVs in microgrids. Existence of equilibrium of the proposed single leader multi-follower game is analyzed. Numerical results demonstrate the effectiveness of the proposed model.

Transportation resilience optimization from an economic perspective at the pre-event stage

Since disruptive events can cause negative impacts on a city's regular traffic order and economic activities, it is crucial that a transport network is resilient against disaster to prevent significant economic losses and ensure regular social, economic, and traffic order. However, using the transport metric for resilience improvement can only provide a limited view of transport pre-investments. This study develops an optimization framework to tackle the problem of resilient road pre-investment with the aim of resilience enhancement of traffic systems from an economic perspective by applying the integrated computable general equilibrium (CGE) model. First, we use the Shapley value, which considers road links’ interact cooperation, to determine critical candidate links that need to be upgraded. Second, we propose the Economic-based Network Resilience Measure (ENRM) as a performance indicator to evaluate network-level resilience from the economic perspective. Third, a bi-level multi-objective optimization model is formulated to identify the optimal capacity improvement for candidate critical links, where the objectives of the upper-level model are to minimize the ENRM and pre-enhancement budget. The lower-level model is built on the integrated CGE model. The genetic algorithm approach is used to solve the proposed bi-level model. A case study of the optimization framework is presented using a simplified Sydney network. Results suggest that a higher budget can help promote people's social welfare and improve transportation resilience. However, the Pareto-optimality is observed, and the marginal utility decreases with an increase in the investment budget. Further, the results also show that investment returns are higher in severe disasters. This study will help transport planners and practitioners optimize resilience pre-event investment strategies by capturing a wider range of project impacts and evaluating their economic impacts under general equilibrium rather than partial economic equilibrium, which is often assumed in traditional four-step transport planning.

Shuttle Bus Line Planning in Response to Unexpected Disruption in Urban Rail Transit Networks

When metro systems need to be temporarily closed due to an unexpected disruption, the metro operators have to arrange shuttle buses as alternative transport for trains, while passengers have to find new routes to complete their journeys. However, the additional shuttle bus lines might be redundant if the well-known phenomenon of the “Braesss Paradox” exists. To address this issue, this paper proposes a bi-level programming model in which the objective of the upper-level model is to minimize the number of shuttle bus lines, while the lower-level model is a UE (User Equilibrium) model that simulates the route choice of passengers. To solve this bi-level programming model, the Overload Arc-oriented Heuristics (OAH) algorithm is developed to find an initial solution, and then we develop a BS (Bi-direction Search) algorithm to obtain the optimal solution to our model. Numerical cases of the partial Beijing Metro network have proved the efficiency and effectiveness of our method, and the result shows that: (1) compared with the standard bus bridging routes, the additional shuttle bus lines can significantly reduce the number of stranded passengers; (2) the number of stranded passengers at each station can be controlled by two strategies: adjust the departure frequency of each shuttle bus line and control the passenger flow at each station.

Superradiance of a Stopped Polarization Pulse in a Thin Layer of a Five-Level Medium Excited by Subcycle Attosecond Pulses

Using the numerical solution of the system of equations for the amplitudes of bound states, together with the wave equation, we theoretically consider stopped polarization pulse superradiance upon excitation by a pair of half-period attosecond pulses in a thin layer of a five-level resonant medium, the parameters of which are the same as in a hydrogen atom. It is shown that in the case of a multilevel medium, at certain parameters of the exciting field, the superradiance pulse near the medium is also a single-cycle pulse, the shape of which is determined by the first time derivative of the stopped polarization pulse, as in the case when approximate low-level and classical models were used to describe the response of the medium. Keywords: superradiance, attosecond pulses, stopped polarization pulse, unipolar pulses, subcycle pulses.

Сверхизлучение импульса остановленной поляризации в тонком слое пятиуровневой среды, возбуждаемой субцикловыми аттосекундными импульсами

Using the numerical solution of the system of equations for the amplitudes of bound states, together with the wave equation, we theoretically consider stopped polarization pulse superradiance upon excitation by a pair of half-period attosecond pulses in a thin layer of a five-level resonant medium, the parameters of which are the same as in a hydrogen atom. It is shown that in the case of a multilevel medium, at certain parameters of the exciting field, the superradiance pulse near the medium is also a single-cycle pulse, the shape of which is determined by the first time derivative of the stopped polarization pulse, as in the case when approximate low-level and classical models were used to describe the response of the medium.

The pricing method for abandoned wind power contract between wind power enterprises and desalination plants in bilateral transactions

In Northeast China’s electric power auxiliary service market, guiding interruptible load users to participate in bilateral transactions is an effective measure to ease the difficulty of grid peak regulation and improve the utilization rate of wind power. Aiming at the lack of theoretical guidance in the current bilateral transactions, this paper proposes a two-stage pricing (TSP) method. Firstly, the freshwater supply and demand balance model of the desalination plant is constructed. The upper-level optimization model of bilateral transaction for profit maximization of the desalination plant is constructed. Then, considering the profit distribution among transaction parties and constraints on wind power utilization, a low-level calculation model of wind power pricing is constructed. Finally, the TSP method is applied to the numerical analysis of bilateral transaction between a desalination plant and a wind power company. The TSP method jointly optimizes the dispatching scheme between the variable speed pump and the water storage tank of the desalination plant. Under the constraints of reasonable profit distribution and wind power utilization, the transaction price finally converges to a range acceptable to both parties. The TSP method can effectively improve the utilization rate of wind power and optimize the flexibility of energy utilization. • A detailed mixed-integer linear programming (MILP) model is developed for desalination plants. • A model for seawater desalination plants to participate in bilateral trading markets is proposed. • A TSP method for calculating the price of bilateral transactions is proposed. • The TSP method can effectively optimize the flexibility of energy utilization.

Структурно-функциональный анализ взаимодействия с организациями частного сектора экономики при ликвидации чрезвычайных ситуаций

Introduction. The article is devoted to the application of Structured Analysis and Design Technique (acronym - SADT) for the formalization of the processes of interaction of the management bodies of the emergency response with private sector organizations in the management of reserves of material resources for emergency response. The relevance lies in improving the decision-making mechanism for the use of material resources of economic entities for emergency response. The scientific significance lies in the formalization of the model of interaction between the management bodies of the Unified State System of Prevention and Liquidation of Emergency Situations and organizations of the private sector of the economy based on the methods of structural programming SADT. The practical significance lies in determining the stages of the construction of the model of interaction between the management bodies of the Unified State System of Prevention and Liquidation of Emergency Situations and organizations of the private sector of the economy, as well as determining a number of models and algorithms for the implementation of the proposed SADT model in a generalized form. The purpose of the study is to identify the relationship between the functions and structure of the elements of the system of interaction between the management bodies of the Unified State System of Prevention and Liquidation of Emergency Situations and organizations of the private sector of the economy in the management of reserves of material resources. Research methods. during the study, the SADT method of structural and functional analysis was used. In the modeling process, together with the IDEF0 standard, the IDEF3 low-level process modeling and analysis standard was used for a more detailed analysis of functional blocks (IDEF3 notation was used to create a workflow model, collect information about the state of the simulated system). Results and its discussion. The interrelation of functions and the structure of the elements of the system of interaction between the management bodies of the Unified State System of Prevention and Liquidation of Emergency Situations and organizations of the private sector of the economy in the management of reserves of material resources are revealed. A structural-functional model of interaction between the management bodies of the Unified State System of Prevention and Liquidation of Emergency Situations and organizations of the private sector of the economy in the management of reserves of material resources is proposed. The place in the general structure of the system material support systems for liquidation of emergency situations of the following models and algorithms has been determined: Decision support model for assessing the sufficiency of produced material resources to eliminate emergencies on the territory of a constituent entity of the Russian Federation; Decision support model algorithm for placing reserves of material resources in the presence of a shortage of commodity stocks; Decision support model algorithm for the formation of reserves of material resources based on the management of insurance stocks of organizations; Decision support model for the delivery of material resources to the emergency area. Conclusions. The use of structural and functional analysis methods for automating the process of managing reserves of material resources can be applied in the development of computer programs and databases for calculating the calculated parameters of the resource security of the emergency response process both in moderation mode and in real time. Keywords: modeling; SADT; IDEF0; IDEF3; reserves of material resources; business entity; liquidation of an emergency.

Optimal Pricing Strategy for Data Center Considering Demand Response and Renewable Energy Source Accommodation

With the continuous development of information technology, data centers (DCs) consume significant and ever-growing amounts of electrical energy. Renewable energy sources (RESs) can act as clean solutions to meet this requirement without polluting the environment. Each DC serves numerous users for their data service demands, which are regarded as flexible loads. In this paper, the willingness to pay and time sensitivities of DC users are firstly explored, and the user-side demand response is then devised to improve the overall benefits of DC operation. Then, a Stackelberg game between a DC and its users is proposed. The upper-level model aims to maximize the profit of the DC, in which the time-varying pricing of data services is optimized, and the lower-level model addresses user's optimal decisions for using data services while balancing their time and cost requirements. The original bi-level optimization problem is then transformed into a single-level problem using the Karush-Kuhn-Tucker optimality conditions and strong duality theory, which enables the problem to be solved efficiently. Finally, case studies are conducted to demonstrate the feasibility and effectiveness of the proposed method, as well as the effects of the time-varying data service price mechanism on the RES accommodation.

Bi-level programming model approach for electric vehicle charging stations considering user charging costs

• A new bi-level planning model is proposed that integrates the interests of both charging station investors and EV users, where the upper model has the global economic return as the optimization objective, and the lower model has the EV user's satisfaction with the charging service (charging cost) as the optimization objective. The global economic cost is optimized while the service satisfaction of the user is improved. • The time cost, economic cost, and mileage anxiety are considered together to characterize the service satisfaction of EV users. Specifically, the charging queuing time, driving distance, desired charging volume, and actual charging volume are used to reflect the charging cost of EV users and to reflect the autonomy of EV users more accurately, and a combination of fast and slow charging posts are used for planning to meet the needs of different users and grid constraints, to improve the operational efficiency of charging stations and reduce the charging queuing time of EV users. • The conventional method and the bi-level planning method are solved separately for a region of Beijing, and the effectiveness of the proposed method is verified by comparing factors such as investors' returns, users' charging costs, and queuing times. The rapid development of electric vehicles (EV) has placed greater demands on the planning and construction of public electric vehicle charging stations (EVCS). As EV users are highly autonomous in their charging behavior, the interests of investors and EV users are mutually affected and challenging to balance. Therefore, this paper proposes a bi-level planning model to balance the interests of investors and EV users and optimize global economic costs while improving the service satisfaction of users. The upper-level model aims to optimize the economic cost. In contrast, the lower-level model aims to optimize the service satisfaction of EV users and characterizes the charging satisfaction of EV users through the costs of charging queuing time, distance traveled, desired to charge volume, and actual charging volume, to more accurately reflect the autonomy of EV users. A combination of fast and slow charging piles is also used for planning to meet the needs of different users and improve charging stations' operational efficiency. Finally, a case study is conducted in an area of Beijing to verify that the optimization model has the advantages of low global economic cost, short charging queuing time for users, and high service satisfaction.

A bi-level humanitarian response plan design model considering equity and efficiency—the example of Yemen

<abstract> <p>Yemen has suffered from a civil war since 2015, which caused the largest famine in the world at this time. People came in need of urgent humanitarian relief in all sectors. In this situation, the donor countries are offering funds to non-profit humanitarian organizations to help Yemen in critical sectors, such as food, health, water, education and other sectors. We propose a new bi-level optimization distribution model for large-scale emergency logistics in Yemen. The upper-level model aims to minimize the unmet demand. The lower-level model seeks to maximize the funds sent to affected areas that fulfill the needs of the affected people by appealing to the donor countries to increase the funds. This model ensures a satisfying rate of equity and efficiency distribution among aid recipients of all governorates of Yemen based on their needs. We consider in this work the top ten donor countries, the nine sectors of the sustainable development goals, the five top humanitarian organizations and twenty-two disastrous regions. The model is applied and validated using actual data collected from Yemen in 2021. The results indicate the necessity of redistributing funds to all governorates of Yemen according to their needs and the priority of the supporting sectors. This proposed model is essential to humanitarian relief decision-makers in general and workers in Yemen in particular as it ensures the continuous flow of aid from donors to beneficiaries and is equitable and effectively distributed. It also gives a glimpse of the importance of continuing to appeal for fundraising from the donors to increase funds and their importance to cover the most significant percentage of those affected.</p> </abstract>

Bi-Level Optimizing Model for Microgrids With Fast Lithium Battery Energy Storage Considering Degradation Effect

The nonlinear degradation effect of the fast lithium battery energy storage system (FLBESS) and the time-scale variability of peak shaving and frequency regulation both make the optimal operation of the microgrid more challenging. Therefore, this paper presents a bi-level optimization model to balance the degradation cost of lithium battery and the benefit of peak shaving and frequency regulation and improve the utilization of FLBESS while dealing with the multiple time scales optimization problems. The upper-level model mainly optimizes the day-ahead hourly power to minimize the power purchase cost and wind and solar power curtailment cost while calculating the internal parameters of the FLBESS to supply the lower-level model for the solution. The lower model optimizes the intra-hour economic cost and coordinates the frequency regulation benefit and lithium battery degradation cost. Finally, case studies are conducted using a regional microgrid to verify that the model solution satisfies the requirements for optimal system operation. In contrast, the model has the advantages of lower economic cost, more significant life extension effect, and higher energy storage utilization rate. The results show that the annual costs were reduced by 14.9%, and the battery life was increased by 19.0% than without considering degradation.

Neuroimaging evidence for the direct role of auditory scene analysis in object perception.

Auditory Scene Analysis (ASA) refers to the grouping of acoustic signals into auditory objects. Previously, we have shown that perceived musicality of auditory sequences varies with high-level organizational features. Here, we explore the neural mechanisms mediating ASA and auditory object perception. Participants performed musicality judgments on randomly generated pure-tone sequences and manipulated versions of each sequence containing low-level changes (amplitude; timbre). Low-level manipulations affected auditory object perception as evidenced by changes in musicality ratings. fMRI was used to measure neural activation to sequences rated most and least musical, and the altered versions of each sequence. Next, we generated two partially overlapping networks: (i) a music processing network (music localizer) and (ii) an ASA network (base sequences vs. ASA manipulated sequences). Using Representational Similarity Analysis, we correlated the functional profiles of each ROI to a model generated from behavioral musicality ratings as well as models corresponding to low-level feature processing and music perception. Within overlapping regions, areas near primary auditory cortex correlated with low-level ASA models, whereas right IPS was correlated with musicality ratings. Shared neural mechanisms that correlate with behavior and underlie both ASA and music perception suggests that low-level features of auditory stimuli play a role in auditory object perception.

ACO+PSO+A*: A bi-layer hybrid algorithm for multi-task path planning of an AUV

Autonomous underwater vehicle (AUV) plays a great role in the ocean engineering, and path planning is one of its key technologies. For such scenarios as oil spill detection, AUV should execute multiple tasks, which become more challenging due to the 3D ocean environment with obstacles. To solve the multi-task path planning problem of AUV, this paper first proposes a bi-level multi-objective path planning model aimed at minimizing the path length and dangerous distance. Then, a bi-layer hybrid algorithm is developed to solve the above model. In this algorithm, ant colony optimization algorithm (ACO) is adopted to generate a task sequence of the upper level model in the outer layer; particle swarm optimization algorithm (PSO) is employed to produce some waypoints between two adjacent tasks, and A* algorithm is used to generate a collision-free path of the lower level model based on waypoints in the inner layer. After that, the collision-free path in the inner layer is feedback to the ACO in the out layer to update its pheromone, and ACO yield a better task sequence in the next iteration, thus obtaining the shortest collision-free path traversing all tasks. Finally, PSO+A* and A* algorithms, together with the proposed bi-layer hybrid algorithm and some two-stage optimization algorithms are compared, respectively. Empirical results show that the proposed algorithm can produce an optimal collision-free path with shorter length and higher security.

Parthenon—a performance portable block-structured adaptive mesh refinement framework

On the path to exascale the landscape of computer device architectures and corresponding programming models has become much more diverse. While various low-level performance portable programming models are available, support at the application level lacks behind. To address this issue, we present the performance portable block-structured adaptive mesh refinement (AMR) framework Parthenon, derived from the well-tested and widely used Athena++ astrophysical magnetohydrodynamics code, but generalized to serve as the foundation for a variety of downstream multi-physics codes. Parthenon adopts the Kokkos programming model, and provides various levels of abstractions from multidimensional variables, to packages defining and separating components, to launching of parallel compute kernels. Parthenon allocates all data in device memory to reduce data movement, supports the logical packing of variables and mesh blocks to reduce kernel launch overhead, and employs one-sided, asynchronous MPI calls to reduce communication overhead in multi-node simulations. Using a hydrodynamics miniapp, we demonstrate weak and strong scaling on various architectures including AMD and NVIDIA GPUs, Intel and AMD x86 CPUs, IBM Power9 CPUs, as well as Fujitsu A64FX CPUs. At the largest scale on Frontier (the first TOP500 exascale machine), the miniapp reaches a total of 1.7 × 1013 zone-cycles/s on 9216 nodes (73,728 logical GPUs) at [Formula: see text] weak scaling parallel efficiency (starting from a single node). In combination with being an open, collaborative project, this makes Parthenon an ideal framework to target exascale simulations in which the downstream developers can focus on their specific application rather than on the complexity of handling massively-parallel, device-accelerated AMR.

Bike-sharing systems rebalancing considering redistribution proportions: A user-based repositioning approach

Bike-sharing systems have become an indispensable transportation mode due to the environmental friendliness and shareability in the sustainable cities development process. However, the asymmetry of people’s travel patterns during the morning and evening rush hours has contributed to the imbalance in bike inventory. Consequently, station rentals and returns require redistribution to address the rebalancing of bikes. In this paper, a user-based repositioning method through a bi-level programming model is proposed. With the objective of minimizing the repositioning workload, the upper-level model yields redistribution proportions that enable the balance between rentals and returns at the station. In addition, aiming at maximum user profit, the lower-level model calculates a redistribution matrix between station pairs and provides recommended stations for users. Finally, three levels of evaluation indicators for the bike-sharing system, operators, and users are presented. The results indicate that the proposed user-based repositioning is remarkably effective in improving the bike inventory balance and the station’s turnover rate. This study provides a novel idea for the bike-sharing repositioning problem and contributes to the improvement of urban transportation.

Bi-level planning model of distributed PV-energy storage system connected to distribution network under the coordinated operation of electricity-carbon market

The disordered connection of Distributed PV-Energy Storage Systems (DPVES) in the Distribution Network (DN) will have negative impacts, such as voltage deviation and increased standby costs, which will affect the demand of urban consumers for reliable and sustainable power consumption. Therefore, reasonable planning of the location and capacity of the DPVES in the DN is one of the key measures to reduce these negative impacts, while promoting the consumption of renewable energy and protecting the income of the DPVES. In this paper, under the background of coordinated operation of China's electricity market and carbon market, considering the uncertainty of distributed photovoltaic (DPV) output power and the demand response (DR) behavior of users, a bi-level planning model of DPVES in DN is established. The upper-level model aims at the maximum revenue of the DPVES in the DN and the highest local consumption rate of DPV, and the decision variables are the connection location and capacity of the DPVES. The lower-level model aims at the minimum average voltage deviation of the DN nodes, and the decision variables are the implementation of load-side DR and the output power of the DPVES. Then, the solution method and process of the model are given. Finally, four planning scenarios are set up in the IEEE-33 node distribution system, and the planning results of different scenarios are analyzed and discussed. The research results show that the bi-level planning model proposed in this paper can reduce the average voltage deviation of DN nodes while effectively increasing the average return of the DPVES and improving the local consumption rate of DPV.

Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems

We analyze the performance portability of the skeleton-based, single-source multi-backend high-level programming framework SkePU across multiple different CPU–GPU heterogeneous systems. Thereby, we provide a systematic application efficiency characterization of SkePU-generated code in comparison to equivalent hand-written code in more low-level parallel programming models such as OpenMP and CUDA. For this purpose, we contribute ports of the STREAM benchmark suite and of a part of the NAS Parallel Benchmark suite to SkePU. We show that for STREAM and the EP benchmark, SkePU regularly scores efficiency values above 80% and in particular for CPU systems, SkePU can outperform hand-written code.