Local Grid Research Articles

Dynamic energy scheduling for end-users with storage devices in smart grid

In this paper, we endeavor to address the problem of dynamic energy scheduling scheme for end-users with storage devices in smart grid. An end-user with an energy storage device is developed, which draws energy from multiple energy sources: local energy suppliers and external power grid. Our goal is to minimize the end-user’s total costs (including energy usage cost and storage cost) over long-term time under uncertainty (time-varying electricity price, uncertain energy output and demand). Concerning the energy storage cost, the resulting problem is modeled as a stochastic optimization case. Following this trend, based on the improved Lyapunov optimization, a dynamic energy scheduling algorithm with lower complexity is developed. It is theoretically proved that the proposed algorithm can make the optimization target asymptotically close to optimum. Simulation results are given to demonstrate that proposed algorithm can significantly save total costs than existing schemes where energy scheduling without the energy storage cost constraint.

Aspects of Determining the Energy Storage System Size Linked to Household-Sized Power Plants in Hungary in Accordance with the Regulatory Needs of the Electric Energy System

The global energy markets of the last decade have been characterized by an ever-increasing share of electric power, more than half of which is projected to come from renewable energy sources by the year 2030. Such a remarkable rise in the quantity of renewable energy, of course, will induce a series of related changes as, without the successful integration of all that unconventional type of energy into the existing energy systems, the sustainability and security of the electricity supply cannot be maintained. As a result, new legislation and energy policies are required all over the world to accommodate not only the latest technological solutions but also a variety of previously unknown market actors. In the institutions, businesses and households of Hungary, the notion of sustainability has been gaining more and more importance lately, which is manifest in the efforts to reduce the use of electricity from the public grid, which is generated by burning fossil fuel. This endeavor is facilitated by the installation of photovoltaic (PV) household-sized power plant (HMKE) systems. Currently, the Hungarian electric energy system does not possess sufficiently flexible capacities; moreover, even this capacity is expected to decrease considerably in the future due to the phasing out fossil fuel power plants. Furthermore, dynamically growing HMKE penetration means an increasing frequency of technical problems in the macroenergy system (e.g., reverse energy flow in the local grid). It is such challenges that energy storage technologies can provide a solution for. Presently, there is insufficient information available on the recommended energy storage size necessary for the efficient integration of Hungarian HMKE systems into the electric energy system and the related investment needs. The innovative novelty of this study is that it examines the quantity and power of Hungarian HMKEs in the districts of the various electric companies over time with a view of exploring a possible way of their efficient integration into the electric energy system by determining the nominal energy storage power and energy capacity of the proposed energy storage systems. In addition, the paper also presents the expected investment needs associated with these energy storage systems.

Flow pattern investigation of bionic fish by immersed boundary–lattice Boltzmann method and dynamic mode decomposition

The investigation of fish swimming is prevalent in the fields of biomimetic hydrodynamics and is important for research on the temporal–spatial evolvement of vortex structures around fish, the design and development of propulsion systems, the shape and structural design of bionic robot fish, and the energy-saving control of schooling robot fish swimming. Conventional numerical simulations of fish swimming depend on mesh establishment and testing. However, the deforming body of a swimming fish largely affects local grids and results in low simulation accuracy due to the uncertainties of mesh resolution and structures. The immersed boundary method adopted in this paper has many advantages, it can efficiently capture the details of the complex dynamics of solid surfaces. Through this method, the fish surface is discretized into Lagrangian points with dynamic coordinates for the performance of complicated dynamic motions. In this work, the immersed boundary–lattice Boltzmann method algorithm with a multi-direct forcing scheme based on Palabos is tested with the cases of flow past a sphere to validate its precision. Then, a function of harmonic oscillation is coupled with fish surface points to perform the level swimming of the RoboTuna fish at different Reynolds numbers. The evolvements of vortex structures around the fish body are analyzed on the basis of the Q-criterion. The processes of the deformation of streamlines around the fish tail into local swirling by tail paddling are revealed, and an angle of approximately 30° between the outer edges of the velocity contour and the line cross of the fish head emerges after the fluid domain develops into a stable state. Then, the data of the fluid fields are subjected to dynamic mode decomposition (DMD), wherein the single mode reveals the presence of up-and-down and axisymmetric patterns behind the fish body. Reconstruction and error calculation are performed to validate the accuracy of the DMD model, then DMD prediction is performed to obtain the flow pattern in the future state and error analysis is conducted. In this work, the mutual effects of the swimming fish and the fluid fields, the formation processes of the vortical fields around the fish tail, and the temporal–spatial evolvements of the structural dynamics of the fluid fields behind the fish body are investigated to provide fundamental information to investigations on propeller systems, flexible propulsion devices, the mechanisms of energy extraction from fluids by the fish tail, and the energy-saving strategies of fish schooling.

Enhancing acid fracture design in carbonate formation using a dynamic up-scaling procedure to convert discrete fracture network to dual continuum

For a low-permeability carbonate formation, the acid fracture process is simulated through coupling a commercial acid fracture simulator (GOHFER) to a finite volume reservoir simulator (IMEX). Unlike LGR (Local grid refinement) approach that suffers from severe convergence problems, a dynamic up-scaling procedure is employed to convert the discrete fracture network (DFN) model into a dual continuum model for our simulation. In this paper, multiple simulations are used to optimize the acid fracture schedule parameters, such as fluid volume, flow rate, perforation location, number of injection steps, and acid type, in order to maximize the effective fracture length. For four points perforation as the relevant operation case in this work, acid fracturing consumes 44 Mgal acid volume at a rate of 25 bpm at a 20 ft interval, resulting in a 3.5-fold increase in well productivity index (PI). Based on experimental relative permeability data, two models of fine and medium grid sizes are employed to be compared with the LGR method. The results have shown that these models are 22 and 54 times faster than LGR, however, the latter has a deviation of less than 5% which is quite acceptable.

Origins of the Intraseasonal Variability of East Asian Summer Precipitation

AbstractAccurate subseasonal prediction of East Asian summer precipitation (EASP) requires a deep understanding of the origins of its intraseasonal variability (ISV). However, the relative contributions to the EASP ISV from local processes, tropical intraseasonal oscillation (ISO), and extratropical influence remain unknown. We conducted a set of numerical experiments with a grid nudging method to confirm the roles of external forcing from mid‐to‐high latitude wave trains and tropical ISO and quantify their relative contributions. The Community Earth System Model can reproduce realistic EASP ISV and associated preceding signals. The tropical and mid‐to‐high latitude forcings account for, respectively, 53% and 40% of the total variance for the two leading ISV modes of EASP. The tropical forcing contributes more significantly to the two leading modes (31% and 40%, respectively) compared to the extratropical forcing (24% and 15%). These external forcings mainly affect EASP regional averages rather than the values of local (grid) scale.

A Method for Evaluating the Maximum Capacity of Grid-Connected Wind Farms Considering Multiple Stability Constraints

Boosting the capacity of grid-connected wind farms will greatly contribute to increasing the share of sustainable energy in the global generation mix. It is imperative to study the way to quantitatively assess the maximum capacity of grid-connected wind farms in combination with power system stability characteristics. In this work, a method to evaluate the maximum capacity of grid-connected wind farms considering the joint constraints of frequency and voltage stability is proposed based on the global intrinsic property of frequency stability and the local characteristic of voltage stability. Firstly, the maximum capacity of grid-connected wind farms in the power grid with high wind power penetration is assessed globally based on the frequency stability constraints, and then locally considering the voltage stability constraints of each local power grid. Further on, a quantitative method to evaluate the capacity of grid-connected wind farms is proposed based on the correlation between the local static voltage stability margin and the local capacity of grid-connected wind farms, as well as the global constraint of the maximum capacity of grid-connected wind farms. Finally, the effectiveness of the proposed method is verified by the simulation results of an actual regional power grid.

WukaStore: Scalable, Configurable and Reliable Data Storage on Hybrid Volunteered Cloud and Desktop Systems

In this paper, we propose a hybrid storage framework WukaStore, which offers a scalable, configurable and reliable big data storage service by integrating stable storage (such as Cloud storage or durable storage utilities) and volatile storage (such as idle storage harnessed from desktop PCs over the Internet). By configuring different storage strategies, WukaStore delivers cost-effective storage service to satisfy users’ requirements. We present trace-driven simulations to study the impact of different strategies and how to ensure high availability and durability in WukaStore. We present the prototype implementation of WukaStore based on BitDew, an open source middleware for Big Data management. We conduct performance evaluations to validate the effectiveness of WukaStore, through the deployment of WukaStore in the French Grid'5000 experimental platform. In particular, we also present a case study where WukaStore is deployed in a hybrid environment taking advantage of storage provided by Amazon S3, Dropbox and a local Desktop Grid at the same time. Our evaluation results show that WukaStore provides users with an alternative method to store their big data on hybrid volunteered cloud and desktop systems and to decrease the cost of data storage, while providing great data access performance, scalability as well as reliability.

Modeling of large capacity condenser based on electromagnetic transient simulation and its impacts on East China Power Grid

With the development of long-distance transmission of higher voltage levels, the loss of reactive power on transmission lines is increasing. The dependence on the external electricity is also rising, so that the voltage stability problems of the receiving system have become increasingly prominent. Therefore, using dynamic reactive compensation technology can improve the operating characteristics of the power grid and improve the safety and stability of the system. Based on the electromagnetic transient data of East China Power Grid in 2025, based on the parameters of the new large-capacity synchronous condenser, the electromagnetic transient model of the synchronous condenser is established and simulated. The simulation results show that after the installation of synchronous condenser, the minimum voltage of ZP bus is improved to different extents, the voltage recovery time is reduced to different extents. It also plays a certain role in reducing the number of commutation failures. Therefore, the installation of the synchronous condenser can provide effective dynamic reactive support for the local power grid with high proportion of DC power, which can reduce the probability of DC commutation failure in the AC grid fault.

Euler-Lagrange simulation of dense gas-solid flow with local grid refinement

Euler-Lagrange method is powerful for studying dense gas-solid flow, where the Eulerian grid is typically 3–5 times of particle diameter to ensure the accuracy of information mapping between gas and solid phases. This condition limits its applications in simulating reactors with complex geometries which require the use of Eulerian grids that are comparative to or smaller than particle diameter. In this study, eight methods for mapping discrete particle information to continuous fluid field were compared first via the simulation of a packed bed, their pros and cons were analyzed and discussed in detail; A kernel function method (the normalized kernel function method II, NKFMII) was then selected to simulate the hydrodynamics and heat transfer of gas-solid bubbling fluidized beds, the results not only validated NKFMII for interphase information mapping but also indicated that a grid-size-independent solution can be achieved; Finally, in order to balance the computational efficiency and accuracy a hybrid particle centroid method (PCM) and NKFMII method was proposed to achieve the interphase information mapping and then to simulate the hydrodynamics of a fluidized bed with immersed tubes, the ability of local grid refinement and the effectiveness of the coupled PCM and NKFMII method were demonstrated. This study proved that Euler-Lagrange simulation with local grid refinement is able to simulate gas-solid reactors with complex geometries.

Analysis of Exponential–Polynomial Single Step Method for Singularly Perturbed Delay Differential Equations

This research presents Exponential – Polynomial Single Step Method (EPSSM), which uses non-linear polynomial interpolating function to solve Singularly Perturbed Delay Differential Equations (SPPDDEs). The stability polynomial of the method is obtained. The Local Grid Search Algorithm termed LGSA is applied in determining the stability region. The efficiency of these methods is compared with the other two numerical methods, namely Runge-Kutta Method (RKM) and Rational Single Step Method (RSM) through two examples of Singularly Perturbed Delay Differential Equations (SPPDDEs).

Situation Awareness by Simple Intuitive Traffic Light Signals for Smart Utilisation of Local Demand and Supply Flexibility

To realise the energy transition, every renewable source shall at least partially contribute to the demand–supply balancing, including customer-owned controllable loads and energy sources. Their commonly small size and spatial occurrence suggests addressing volatility issues locally, using local flexibilities to mitigate their impact. This calls for simple and effective signalling that enables interaction among local stakeholders, including local producers and customers. According interfaces and information formats appear to not yet exist. In this article, we propose a traffic-light-like system that enables the local grid operator to trigger situation-aware customer behaviour, supporting grid stability when needed and, in return, allowing customers to fully exploit temporary grid capacity when no safety or stability issues persist. The applied intuitive deduction method based on existing coordination mechanisms and objectives indicates, without proof, that the proposed granular traffic light system can enable the distribution grid flexibility required to facilitate more renewable energy being produced and inserted by local customers, to relieve grid levels above from transporting and equalising volatile energy shares, and to improve the economics of distributed renewable energy sources.

A Fluid Model of an Electric Vehicle Charging Network

We develop and analyze a measure-valued fluid model keeping track of parking and charging requirements of electric vehicles in a local distribution grid. We show how this model arises as an accumulation point of an appropriately scaled sequence of stochastic network models. Our analysis incorporates load-flow models that describe the laws of electricity. Specifically, we consider the alternating current (AC) and the linearized Distflow power flow models and show a continuity property of the associated power allocation functions.

Analysis of Multi-Frequency Oscillation Stability in a Prosumer Power Network

Multi-frequency oscillation is a new type of electromagnetic oscillation issue in power systems caused by the increasing penetration of renewable power and power electronic devices. This study investigates the risks and influencing factors of multi-frequency oscillation in a prosumer power network where a variety of converter-based resources exists. For the feasibility of analysis, the internal and external stability of the study system are defined and analyzed based on sequence impedance models. Analysis results show the impacts of control parameters of prosumers, length of cables, transformer ratios, local grid strength, and power and capacity of prosumers on the risks of oscillation. Accordingly, despite the poorly tuned control parameters, the study system has higher risks of multi-frequency oscillation with longer cables, lower-rated voltage of cables, larger capacity, and inductive power consumption of the neighboring prosumers. Frequency-domain analysis results are demonstrated by EMTDC/PSCAD simulations.

Hydrogen in Grid Balancing: The European Market Potential for Pressurized Alkaline Electrolyzers

To limit the global temperature change to no more than 2 °C by reducing global emissions, the European Union (EU) set up a goal of a 20% improvement on energy efficiency, a 20% cut of greenhouse gas emissions, and a 20% share of energy from renewable sources by 2020 (10% share of renewable energy (RE), specifically in the transport sector). By 2030, the goal is a 27% improvement in energy efficiency, a 40% cut of greenhouse gas emissions, and a 27% share of RE. However, the integration of RE in energy system faces multiple challenges. The geographical distribution of energy supply changes significantly the availability of the primary energy source (wind, solar, water) and is the determining factor, rather than where the consumers are. This leads to an increasing demand to match supply and demand for power. Especially intermittent RE like wind and solar power face the issue of energy production unrelated to demand (issue of excess energy production beyond demand and/or grid capacity) and forecast errors leading to an increasing demand for grid services like balancing power. Megawatt electrolyzer units (beyond 3 MW) can provide a technical solution to convert large amounts of excess electricity into hydrogen for industrial applications, substitute for natural gas, or the decarbonization of the mobility sector. The demonstration of successful MW electrolyzer operation providing grid services under dynamic conditions as request by the grid can broaden the opportunities of new business models that demonstrate the profitability of an electrolyzer in these market conditions. The aim of this work is the demonstration of a technical solution utilizing Pressurized Alkaline Electrolyzer (PAE) technology for providing grid balancing services and harvesting Renewable Energy Sources (RES) under realistic circumstances. In order to identify any differences between local market and grid requirements, the work focused on a demonstration site located in Austria, deemed as a viable business case for the operation of a large-scale electrolyzer. The site is adapted to specific local conditions commonly found throughout Europe. To achieve this, this study uses a market-based solution that aims at providing value-adding services and cash inflows, stemming from the grid balancing services it provides. Moreover, the work assesses the viability of various business cases by analyzing (qualitatively and quantitatively) additional business models (in terms of business opportunities/energy source, potential grid service provision, and hydrogen demand) and analyzing the value and size of the markets developing recommendations for relevant stakeholder to decrease market barriers.

A techno-economic analysis of a solar PV and DC battery storage system for a community energy sharing

Energy harvesting from renewable sources can play a vital role to decarbonize the environment, limit global warming and mitigate the growing energy demand. The objective of this work consists of decarbonizing a University Campus and neighboring communities by producing electricity from solar photovoltaic systems integrated with an energy storage system and local grid station. A new mathematical model is developed to maximize the system power generation and balance the load demand. The simulation and optimization software System Advisor Model (SAM) is used to develop and test model results. The software is used to analyze and optimize the solar energy generation, the energy demand, and the economic performance: capital cost, overall investment, net present value, and the Levelized Cost of Energy of the project. A novel approach decentralized load centers is adopted to share power with adjacent communities. At the aim of improving the system flexibility, reliability, and climate resilience, the established model is grid-connected. The CO2 emissions reduction is also determined to evaluate the environmental impact of the interventions.

Multi-Phase Rate Transient Behaviors of the Multi-Fractured Horizontal Well With Complex Fracture Networks

Abstract Complex fracture networks (CFN) provide flow channels and significantly affect well performance in unconventional reservoirs. However, traditional rate transient analysis (RTA) models barely consider the effect of CFN on production performance. The impact of multi-phase flow on rate transient behaviors is still unclear especially under CFN. Neglecting these effects could cause incorrect rate transient response and erroneous estimation of well and fracture parameters. This paper investigates multi-phase rate transient behaviors considering CFN and tries to investigate in what situations the multi-phase models should be used to obtain more accurate results. First, an embedded discrete fracture model (EDFM) is generated instead of Local Grid Refinement method to overcome time-intensive computation. The model is coupled with reservoir models using non-neighboring connections (NNCs). Second, eight cases are designed using the EDFM technology to analyze effect of natural fractures, formation permeability, and relative permeability on rate transient behaviors. Third, Blasingame plot, log–log plot, and linear flow plot are used to analyze the differences of rate transient response between single-phase and multi-phase flow in reservoirs with CFN. For multi-phase flow, severe deviations can be observed on RTA plots compared with single-phase model. Combination of three RTA type curves can characterize the differences from early to late flow regimes and improve the interpretation accuracy as well as reduce the non-unicity. Finally, field data analysis in Permian Basin demonstrates that multi-phase RTA analysis are required for analyzing production and pressure data since single-phase RTA analysis will lead to big errors especially under high water cut during fracturing fluid flowback period, early production of unconventional gas wells or after waterflooding, or water huff-n-puff.

HLocalExp-CM: confidence map by hierarchical local expansion moves for accurate stereo matching

We present a stereo matching approach referred to as HLocalExp-CM by exploiting the hierarchical local contextual information and a confidence map based on a new grid structure. The proposed approach preserves fine depth edges and extracts accurate disparities in weak texture, textureless, and repeated texture regions. The proposed approach adopts a two-stage optimization strategy. In the framework of first stage, a multiresolution cost aggregation is minimized to reduce the search space of the disparity plane of each pixel. The second stage iteratively optimizes the confidence map and a global energy function to progressively improve the disparity accuracy for each pixel. The confidence map is estimated through classifying the pixels into distinctive and ambiguous ones by computing the decreasing rate of the multiresolution cost aggregation and then performs a spatial propagation and plane refinement for the update of the disparity of each pixel, thereby successfully eliminating the ambiguity of nondistinctive pixels. The global energy function based on a pairwise Markov random field uses cross-scale cost aggregation for taking advantage of context information of objects in different scenarios on local grid regions, which is different from the deep learning technique uses convolution layers extracting the context information. The proposed approach is evaluated on Middlebury benchmark V3, and is ranked first based on “bad 2.0 all metric,” a widely used criterion for the evaluation of stereo images, while the eighth place on “bad 2.0 nonocc metric” (recorded on July 24, 2021).

Implementation of Charging Stations for Hybrid and Electrical Ferries in Croatian Ports

An important aspect of introducing hybrid or all-electric ferries on coastlines is to analyze the supporting land-based energy infrastructure to determine if it is possible to implement charging systems that such vessels rely on. The battery energy storage systems on such vessels will need to be rapidly recharged as passengers and vehicles disembark, which means that the flow of electricity through the distribution grid will be much higher and may lead to power quality issues on the local grid. Once implemented, shore connection and battery charging systems must be safe for both people and connected equipment. The issue of implementing shore connections needs to be analyzed from a technical, economic, and legal perspective. This paper presents the challenges and problems of implementing charging stations for ferries in Croatian ports as a result of the research conducted within the project METRO - Maritime Environment-Friendly Transport Systems.

Optimized design and simulation of a hybrid storage system based on hydrogen as an energy carrier

The integration of renewable energy sources into the electricity system can contribute to the development of a low-carbon economy. However, due to the intermittency and non-programmability of these sources, problems related to the management of local electricity grids may occur. A possible solution or limitation to these issues is given by the electrical storage. In addition, in the next future, domestic micro-grids are expected to play a fundamental role in electric power networks, driving both the academic and industrial research interests in developing highly efficient and reliable conversion and storage technologies. In this study, the behavior of a small-scale hybrid energy system for hydrogen production and storage has been predicted, by means of a developed calculation model, and the operational strategy of the system has been optimized with the aim to maximize the hydrogen production. In addition, with the aim to maximize the overall solar-to-hydrogen chain efficiency, the whole system model has been applied to different operating scenarios, to identify the optimal management strategy to control it.

Bias-Induced Point Auto-Encoder and Comparative Analysis of Point Encoder-Decoder Combinations

As a combination of a point encoder and a decoder, a point auto-encoder (AE) facilitates the reconstruction and segmentation of the point cloud representation of 3D objects. In this paper, first, we present a novel approach to point decoding, referred to here as bias-induced point decoding, which learns pointwise decoding of the same global feature by the layer-wise control of mapping biases while sharing mapping weights, instead of pointwise differentiating the input by concatenating local features or grids to the global feature as is done conventionally. Then, in-depth comparative analyses of 12 possible encoder-decoder combinations are conducted to identify the strengths and weaknesses in terms of accuracy and robustness in reconstruction and segmentation. We verified that a bias-induced point AE could be a viable alternative to conventional point AEs with its own strength and weakness. Finally, the effectiveness of the proposed bias-induced point AE is demonstrated based on its application to the automatic transformation from partial-to-full 3D point cloud representations.