Local Grid Research Articles

Impact of Electric Bus Charging on Distribution Substation and Local Grid in Warsaw

Electric buses are increasingly appearing on the streets of cities around the world. Thus, it is necessary to consider the impact of their charging on the distribution system operation, especially near the charging point. This article presents the problems that may arise while new charging points are connected. Research was carried out on the existing charging point at Spartańska Street in Warsaw, which allowed to obtain daily bus charging profiles and voltage curves. The authors then proposed an exemplary model of a bus terminus with the designed infrastructure for charging buses, based on the assumptions of the public transport operator in Warsaw. The comparison of these two solutions was made and based on it, a methodology of calculating daily demand for any terminus was prepared. In addition, no problems with the power quality were found during the research. This allows us to state that the introduction of electric buses into the fleet of passenger carriers will have a minor impact on the operation of the power system in Warsaw.

Multiresolution Grid Connectivity-Based Transform for Efficient History Matching of Unconventional Reservoirs

Summary Proper characterization of heterogeneous rock properties and hydraulic fracture parameters is essential for optimization of well spacing and reliable estimation of estimated ultimate recovery (EUR) in unconventional reservoirs. High resolution characterization of matrix properties and complex fracture parameters require efficient history matching of well production and pressure response. We propose a novel reservoir model parameterization method to reduce the number of unknowns, regularize the ill-posed problem, and enhance the efficiency of history matching of unconventional reservoirs. The proposed method makes a low-rank approximation of the spatial distribution of reservoir properties taking into account the varying model resolution of the matrix and hydraulic fractures. Typically, hydraulic fractures are represented with much higher resolution through local grid refinements compared to the matrix properties. In our approach, the spatial property distribution of both matrix and fractures is represented using a few parameters via a linear transformation with multiresolution basis functions. The parameters in transform domain are then updated during model calibrations, substantially reducing the number of unknowns. The multiresolution basis functions are constructed by using Eigen-decomposition of an adaptively coarsened grid Laplacian corresponding to the data resolution. Higher property resolution at the area of interest through the adaptive resolution control while keeping the original grid structure improves quality of history matching, reduces simulation runtime, and improves the efficiency of history matching. We demonstrate the power and efficacy of our method using synthetic and field examples. First, we illustrate the effectiveness of the proposed multiresolution parameterization by comparing it with traditional methods. For the field application, an unconventional tight oil reservoir model with a multistage hydraulic fractured well is calibrated using bottomhole pressure and water cut history data. The hydraulic fractures as well as the stimulated reservoir volume (SRV) near the well are represented with higher grid resolution. In addition to matrix and fracture properties, the extent of the SRV and hydraulic fractures are also adjusted through history matching using a multiobjective genetic algorithm. The calibrated ensemble of models are used to obtain bounds of production forecast. Our proposed method is designed to calibrate reservoir and fracture properties with higher resolution in regions that have improved data resolution and higher sensitivity to the well performance data, for example the SRV region and the hydraulic fractures. This leads to a fast and efficient history matching workflow and enables us to make optimal development/completion plans in a reasonable time frame.

Multiwavelet-based mesh adaptivity with Discontinuous Galerkin schemes: Exploring 2D shallow water problems

In Gerhard et al. (2015a) a new class of adaptive Discontinuous Galerkin schemes has been introduced for shallow water equations, including the particular necessary properties, such as well-balancing and wetting-drying treatments. The adaptivity strategy is based on multiresolution analysis using multiwavelets in order to encode information across different mesh resolution levels. In this work, we follow-up on the previous proof-of-concept to thoroughly explore the performance, capabilities and weaknesses of the adaptive numerical scheme in the two-dimensional shallow water setting, under complex and realistic problems. To do so, we simulate three well-known and frequently used experimental benchmark tests in the context of flood modelling, ranging from laboratory to field scale. The real and complex topographies result in complex flow fields which pose a greater challenge to the adaptive numerical scheme and are computationally more ambitious, thus requiring a parallelised version of the aforementioned scheme. The benchmark tests allow to examine in depth the resulting adaptive meshes and the hydrodynamic performance of the scheme. We show that the scheme presented by Gerhard et al. (2015a) is accurate, i.e., allows to capture simultaneously large and very small flow structures, is robust, i.e., local grid refinement is controlled by just one parmeter that is auotmatically chosen and is more efficient in terms of the adaptive meshes than other shallow-water adaptive schemes achieving higher resolution with less cells.

Modeling and frequency control of community micro-grids under stochastic solar and wind sources

The Community Micro-Grid (CMG) is a coordinated local grid area served by one or more distribution substations supported by local renewable and other distributed energy resources (DER). In an islanded mode, the CMG stability reduces due to low inertia of the equivalent system and stochastic nature of renewable energy sources (RESs). To study the frequency stability of the islanded CMG system, this paper explores the mathematical modeling aspects of different sources in the CMG and the robust control design for the community microgrid model. The robust design using a fixed structure H∞ synthesis method has been presented to compensate for the effect of modeling uncertainty. The uncertainty in the CMG model results in parametric perturbation which degrades its performance and stability. This paper explores the existing mathematical models of CMG’s and different control techniques applied for frequency regulation. Robust controller design for CMG is proposed that can handle the stochastic input disturbances like a sudden change in power coming from solar and wind sources and also the model uncertainty that results in the parametric perturbations. The complete model is simulated using MATLAB Simulink platform and results of frequency deviation obtained by robust and PID controller are compared. The controller hardware in loop (C-HIL) validation of the robust control method for CMG has been done using a real-time controller board (DS1104). This CHIL system also implements the CMG plant-controller model and analyzes the frequency deviation against load and renewable power fluctuations. The oscillations in frequency deviation are analyzed for sudden rise or fall in the renewable power coming from the solar and wind sources. A reduction of 30% is achieved in frequency overshoot and settling time using a robust controller than the PID controller. The controller developed and implemented using H∞ synthesis has robust stability and performance for the perturbed CMG model and also shows a better time response, unlike the PID controller.

An implicit local time-stepping method based on cell reordering for multiphase flow in porous media

We discuss how to introduce local time-step refinements in a sequential implicit method for multiphase flow in porous media. Our approach relies heavily on causality-based optimal ordering, which implies that cells can be ordered according to total fluxes after the pressure field has been computed, leaving the transport problem as a sequence of ordinary differential equations, which can be solved cell-by-cell or block-by-block. The method is suitable for arbitrary local time steps and grids, is mass-conservative, and reduces to the standard implicit upwind finite-volume method in the case of equal time steps in adjacent cells. The method is validated by a series of numerical simulations. We discuss various strategies for selecting local time steps and demonstrate the efficiency of the method and several of these strategies by through a series of numerical examples.

A Geothermal-Solar Hybrid Power Plant with Thermal Energy Storage

The concept of a geothermal-solar power plant is proposed that provides dispatchable power to the local electricity grid. The power plant generates significantly more power in the late afternoon and early evening hours of the summer, when air-conditioning use is high and peak power is demanded. The unit operates in two modes: a) as a binary geothermal power plant utilizing a subcritical Organic Rankine Cycle; and b) as a hybrid geothermal-solar power plant utilizing a supercritical cycle with solar-supplied superheat. Thermal storage allows for continuous power generation in the early evening hours. The switch to the second mode and the addition of solar energy into the cycle increases the electric power generated by a large factor—2 to 9 times—during peak power demand at a higher efficiency (16.8%). The constant supply of geothermal brine and heat storage in molten salts enables this power plant to produce dispatchable power in its two modes of operation with an exergetic efficiency higher than 30%.

Control the Voltage Instabilities of Distribution Lines using Capacitive Reactive Power

The voltage instabilities in the distribution lines are primarily related to the integration of photovoltaic power plants with the local grids. Conventional tap-changers cannot compensate for the rapid disparities between generated and consumed power because of sluggish dynamic response. This article presents an effective method and control algorithm to improve the voltage instabilities of distribution lines. Analytical calculation confirms that the application of capacitive reactive power on load is beneficial to keep the voltage at the permissible level. Importantly, the severe concern about the current increment with voltage enhancement is also addressed. The dynamic behavior during capacitance switching is studied using simulation experiments. It is suggested that capacitance is connected to the load for the only time of voltage drop until the transformation ratio changes to the desired level. This article provides an explanation and solution for voltage deviations of electricity distribution lines in steady-state and dynamic modes.

Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs

In this paper, we address the problem of the efficient and sustainable operation of data centers (DCs) from the perspective of their optimal integration with the local energy grid through active participation in demand response (DR) programs. For DCs’ successful participation in such programs and for minimizing the risks for their core business processes, their energy demand and potential flexibility must be accurately forecasted in advance. Therefore, in this paper, we propose an energy prediction model that uses a genetic heuristic to determine the optimal ensemble of a set of neural network prediction models to minimize the prediction error and the uncertainty concerning DR participation. The model considers short term time horizons (i.e., day-ahead and 4-h-ahead refinements) and different aspects such as the energy demand and potential energy flexibility (the latter being defined in relation with the baseline energy consumption). The obtained results, considering the hardware characteristics as well as the historical energy consumption data of a medium scale DC, show that the genetic-based heuristic improves the energy demand prediction accuracy while the intra-day prediction refinements further reduce the day-ahead prediction error. In relation to flexibility, the prediction of both above and below baseline energy flexibility curves provides good results for the mean absolute percentage error (MAPE), which is just above 6%, allowing for safe DC participation in DR programs.

Adjoint method acceleration protocols for model maturation to update static models with time-lapse reservoir surveillance data

We develop an ensemble model-maturation method that is based on the Randomized Maximum Likelihood (RML) technique and adjoint-based computation of objective function gradients. The new approach is especially relevant for rich data sets with time-lapse information content. The inversion method that solves the model-maturation problem takes advantage of the adjoint-based computation of objective function gradients for a very large number of model parameters at the cost of a forward and a backward (adjoint) simulation. The inversion algorithm calibrates model parameters to arbitrary types of production data including time-lapse reservoir-pressure traces by use of a weighted and regularized objective function. We have also developed a new and effective multigrid preconditioning protocol for accelerated iterative linear solutions of the adjoint-simulation step for models with multiple levels of local grid refinement. The protocol is based on a geometric multigrid (GMG) preconditioning technique. Within the model-maturation workflow, a deep-learning technique is applied to establish links between the mesh-based inversion results (e.g., permeability-multiplier fields) and geologic modeling parameters inside a static model (e.g., object dimensions, etc.). Our workflow integrates the learnings from inversion back into the static model, and thereby, ensures the geologic consistency of the static model while improving the quality of the ensuing dynamic model in terms of honoring production and time-lapse data, and reducing forecast uncertainty. This use of deep learning (DL) to post-process the model-maturation outcome effectively converts the conventional continuous-parameter history-matching result into a discrete tomographic inversion result constrained to geological rules encoded in training images.We demonstrate the practical utilization of the adjoint-based model-maturation method on a large time-lapse reservoir-pressure data set using an ensemble of full-field models from a reservoir case study. The model-maturation technique effectively identifies the permeability modification zones that are consistent with alternative geological interpretations and proposes updates to the static model. Upon these updates, the model not only agrees better with the time-lapse reservoir-pressure data but also better honors the tubing-head pressure as well as production logging data. We also provide computational performance indicators that demonstrate the accelerated convergence characteristics of the new iterative linear solver for adjoint equations.

A Load Flow Analysis Method for Kufa Cement Plant

The energy needs have been enlarged extremely. The electricity power generators are utilized and distributed in the national (local) grid. Many factors can affect on national distribution grid stability, such as load flow. It is utilized to evaluate various operating states for energy generation and distribution systems. In this article, six different generators are distributed in Kufa (Iraq) cement plant based on load flow balancing. Behinds, these distributed generators work under two modes, such that island mode and regular operation. The proposed modules are analyzed using Electrical Transient Analyzer Program (ETAP) software. The achieved analysis can help to reduce the distribution grid shutdown. Furthermore, the load balancing can be achieved at both modes. Load flow analysis takes consideration for the total energy demands and losses of the system separately in order to balance load and optimize operation. The results show that the buses’ voltage drop in island mode was more than the voltage drop when the local grid connected to the national grid. The problems of drop voltages and power factor were solved.

Distributed multi-period three-phase optimal power flow using temporal neighbors

The penetration of distributed generation in medium (MV) and low (LV) voltage distribution grids has been steadily increasing every year in multiple countries, thus creating new technical challenges in grid operation and motivating developments in distributed optimization for flexibility management. The traditional centralized optimal power flow (OPF) algorithm can solve technical constraints violation. However, computational efficiency, new technologies (e.g., edge computing) and control architectures (e.g., web-of-cells) are demanding for distributed approaches. This work formulates a novel distributed multi-period OPF for three-phase unbalanced grids that is essential when integrating energy storage units in operational planning (e.g., day-ahead) of LV or local energy community grids. The decentralized constrained optimization problem is solved with the alternating direction method of multipliers (ADMM) adapted for unbalanced LV grids and multi-period optimization problems. A 33-bus LV distribution grid is used as a case-study in order to define optimal battery storage scheduling along a finite time horizon that minimizes overall grid operational costs, while complying with technical constraints of the grid (e.g., voltage and current limits) and battery state-of-charge constraints.

Research on the Calculation Method of Regional Grid Construction Efficiency and Power Demand under the Background of High Power Grid Complexity

With the gradual development of power grid, the characteristics of power grid, such as regionalization, multi-dimensional and network complexity, have become more and more obvious. At the same time, the new round of power system reform has higher requirements for the development of power grid in all aspects. One of the key points of the reform is to achieve accurate investment in power grid, improve the efficiency of power grid construction and meet the demand of power grid construction. In this paper, the classic Analytic Hierarchy Process (AHP) is used, combined with the development situation of the power grid under the new requirements, the index system and model for the calculation of the construction efficiency and demand of the local and municipal power grid under the background of the highly complex development of the power grid are put forward. The model takes the time line of the power grid construction as the axis, through the pre-evaluation and post-evaluation of the power grid construction, the calculation of the construction situation of the regional power grid is completed. The efficiency and demand of power grid construction in different cities are analyzed. The example shows that the model can effectively identify the construction attributes of each region, reflect the construction requirements of the provincial power company system through different judgment matrix, and verify the final calculation results, optimize the construction and demand of the power grid system. The model effectively improves the operation efficiency of the power grid system, and realizes the ultimate goal of energy conservation and emission reduction.

Impact Optimization of Battery Energy Storage System in Microgrid Operation

In microgrid operation, one of the most vital tasks of the system control is to wiselydecide between selling excess power to the local grid or charge the Battery Energy Storage System (BESS). Our study uses Mixed-Integer Linear Programming to investigate the impact of storage system on the operational cost of a microgrid. The results suggested that the presence of BESS would relieve the pressure on the utility grid but not the cost of electricity due to the expensive nature of the storage plant. In view of this, it will be more beneficial to sell excess renewable generated power to the utility grid than to invest in a storage system for larger microgrids.

Impact Optimization of Battery Energy Storage System in Microgrid Operation

In microgrid operation, one of the most vital tasks of the system control is to wiselydecide between selling excess power to the local grid or charge the Battery Energy Storage System (BESS). Our study uses Mixed-Integer Linear Programming to investigate the impact of storage system on the operational cost of a microgrid. The results suggested that the presence of BESS would relieve the pressure on the utility grid but not the cost of electricity due to the expensive nature of the storage plant. In view of this, it will be more beneficial to sell excess renewable generated power to the utility grid than to invest in a storage system for larger microgrids.

Investigation of different production performances in shale gas wells using assisted history matching: Hydraulic fractures and reservoir characterization from production data

We investigated the difference in production performances of three shale gas wells with different completions and fracturing designs. We used assisted history matching technique to perform production match automatically and obtain multiple history matching solutions. The history matching algorithm used in this study is neural networks Markov chain Monte Carlo. In addition, we utilized embedded discrete fracture model technique to model hydraulic fractures instead of local grid refinement method to speed up the simulation runs. The history matching parameters consist of fracture half-length, fracture height, fracture conductivity, fracture width and fracture water saturation for hydraulic fractures properties and include matrix porosity, matrix permeability and relative permeability curves for matrix properties. We found that fracture width, fracture half-length, fracture conductivity and matrix permeability were significantly different in three shale gas wells while fracture height, fracture water saturation, porosity and relative permeability curves were less different. The information from this study will be used further to improve completion and fracturing design.

Uncertainty Estimates for Sea Surface Temperature and Land Surface Air Temperature in NOAAGlobalTemp Version 5

AbstractThis analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.

A local grid refinement scheme for B‐spline material point method

SummaryA local grid refinement scheme for the material point method with B‐spline basis functions (BSMPM) is developed based on the concept of bridging domain approach. The fine grid is defined in the local large‐deformation regions to accurately capture the complex material responses, whereas other spatial domains are discritized by coarse grids. In the overlapping domain between the fine and coarse grids, the constraint of particle displacements obtained with different grids is enforced using the Lagrange multiplier method to eliminate the spurious stress reflection at the fine/coarse grid interface. Representative numerical examples have shown that the BSMPM simulations with the proposed local grid refinement scheme could provide the solutions in good agreement with those obtained with the uniformly fine grid, and that no significant spurious stress reflection is induced at the fine/coarse grid interface, even for the bridging domain size as small as the cell size of the fine grid. It is also found that the proposed local grid refinement method can significantly reduce the BSMPM computational time compared with the cases for uniformly fine grids. A multitime‐step algorithm is presented and shown to considerably enhance the efficiency of the present local grid refinement scheme with no compromise in accuracy.

Single-Step Arbitrary Lagrangian–Eulerian Discontinuous Galerkin Method for 1-D Euler Equations

We propose an explicit, single-step discontinuous Galerkin method on moving grids using the arbitrary Lagrangian–Eulerian approach for one-dimensional Euler equations. The grid is moved with the local fluid velocity modified by some smoothing, which is found to considerably reduce the numerical dissipation introduced by Riemann solvers. The scheme preserves constant states for any mesh motion and we also study its positivity preservation property. Local grid refinement and coarsening are performed to maintain the mesh quality and avoid the appearance of very small or large cells. Second, higher order methods are developed and several test cases are provided to demonstrate the accuracy of the proposed scheme.

Toward a strategic management perspective on local content in African extractives: MNC procurement strategies between local responsiveness and global integration

ABSTRACTLocal content requirements – i.e. government backed requirements that extractive MNCs must procure inputs locally – are fast becoming a major issue in MNC-host country bargaining in Africa. As a result of increasingly stringent local content requirements, extractive MNCs operating in Africa are facing a rapidly evolving strategic field, the management of which may have huge implications for their profitability and efficiency. While a vibrant and dynamic literature on local content in Africa is emerging, this literature is predominantly informed by economic and political perspectives, and strategic management perspectives are virtually absent. Hence, the aim of the paper is to characterize and develop the strategic management perspective on local content. Based on the classical local responsiveness-global integration grid, a framework is developed for, how MNCs may strategize on local content. The paper contributes to research by providing a conceptual framework that can inspire future strategic management research on MNC local content practices in Africa. Moreover, by providing a theory-based understanding of the strategic opportunities and challenges that face MNCs in relation to local content requirements, the paper may inform policymakers on how to better align local content interventions with MNC strategies and interests thus rendering them more effective.

Emergency island operation of a medium-voltage utility grid with a large battery

To achieve a future secure and fully renewable electricity supply, the authors suggest renewable-powered subsystems, which balance demand and supply within their local grid and, in emergency, run in an island operation. The utility of Versorgungsbetriebe Bordesholm (VBB) usually operate their battery energy storage system (BESS) of 15 MWh/12,5 MW realised by RES Deutschland GmbH on the frequency containment reserve (FCR) market. This study shows how the BESS’s power converter bank made by SMA is able to control grid voltage and frequency while switching into island operation without interruption. In addition, it can balance distributed renewable generators (PV and biomass) and the demand of up to 4 MW in Bordesholm during island operation. In preliminary experiments the BESS was able to manage artificial load steps of up to 4 MW without significant disturbances. The final real-word experiment showed that the transition into islanding operation and back is smoothly possible without any voltage disturbances noticed by the customers of VBB. It is a milestone in the energy transition process to be able to uninterruptedly supply the customers of such a utility as VBB only with renewable energy sources and even in case of an upstream grid outage.