Utility Point Of View Research Articles

Financial Implications of Rooftop Solar Penetration in Sri Lanka from Utility Point of View

Solar is one of the fast growing and economical renewable power generation sources. The intention of development of solar power generation is to promote clean energy while addressing the basic requirement of uninterrupted and reliable electricity supply.The Sri Lankan government decided to adopt a policy that would use subsidies to encourage the growth of solar PV-based electricity. As a result, the market developed with a large number of customers eager to install solar rooftop systems, and they received strong assistance from solar power service providers. Hence, the utility is required to absorb the solar energy produced and this study focuses on the impact of solar penetration to the utility.System dispatch data for year 2019 and rooftop solar generation data for a period of 6 months of year 2019 were considered for the analysis in this paper. The model compares the financials of two scenarios to estimate the impact to the utility. The base case scenario, which is business as usual with the already installed solar generation in the system and No solar scenario which assumes that there is no solar in the system and therefore the demand is met by other available generation capacities in the system.This paper examines the two scenarios with careful calculations of how the system can still run without solar in the system. Daily demand patterns were also analysed and then expanded to months and summarized for the year. This research focuses the financial impact of solar electricity penetration to the national grid and how everyone can still be benefitted.

Evaluating User Experience in the Context of Cultural Heritage Dissemination Using Extended Reality: A Case Study of the Dacian Bronze Matrix with Hollow Design

Cultural institutions are increasingly prioritizing the utilization of diverse mixed reality technologies to enrich the visitor experience during their physical exhibitions. These institutions are actively integrating virtual assets to enhance interactivity and facilitate immersive storytelling experiences. The use of extended reality technologies in cultural heritage dissemination has become a common solution to improve the perception on cultural heritage of their visitors. The objective of the proposed research is to conduct a comparative analysis of three distinct extended reality applications used in cultural heritage experiences. The proposed workflow integrates advanced 3D scanning technology and additive manufacturing techniques to produce tangible replicas which are further enhanced using extended reality technologies, such as augmented reality, desktop virtual reality, and immersive virtual reality. To evaluate the developed extended reality applications, we have conducted various System Usability Scale tools to assess applications’ usability while also trying to identify the most appropriate application that can be integrated within the museum exhibition. From a utility point of view, we found no notable differences in the user perceptions between proposed solutions, whereas from a usability and satisfaction point of view, the most preferred solution was the augmented reality one. The workflow is presented in sufficient detail to ensure the replication of the results.

Confidence Interval: Advantages, Disadvantages and the Dilemma of Interpretation.

Confidence interval (CI) is one of the important reporting tools for research data as it not only provides valuable information about the effect size along with its width but also possible clinical significance. Unfortunately, this approach is not being utilized to its fullest extent. Determining point estimate always includes an element of uncertainty due to associated sampling error. A confidence interval may be an appropriate tool to measure this uncertainty. Further, the P value does not convey information about the magnitude of an effect and the error associated with it. Thus, in an ideal situation effect size should preferably be associated with a confidence interval to assess precision. Not only does CI let us assess likely effects but also decides whether the intervention applied could have clinical utility. In contrast, the p-value limits our option to either reject any differences that are not significant or accept those that are. However, confidence intervals are commonly misinterpreted. It is imperative to understand that the CI is not the range of effects that 95% of patients in the population exhibit. Moreover, it would also be erroneous to say that there is a 95% probability that the CI includes the true population effect. Interpretation is usually based on the context in which the confidence interval is being looked at. From a utility point of view and like other statistical tools confidence interval approach does have several advantages as well as disadvantages and is far beyond being a perfect statistical tool.

Regret-Theoretic Multiattribute Decision-Making Model Using Three-Way Framework in Multiscale Information Systems.

The existing multiattribute decision-making (MADM) methods on multiscale information systems (MSISs) are generally studied from the utility point of view, which may cause two problems: 1) the objects are strictly classified into good or bad, which may lead to misclassification and 2) the risk attitude and psychological behaviors of decision makers are difficult to be reflected. In light of this, this article proposes a wide three-way decision (3WD) model on an MSIS, which combines 3WD theory and regret theory and can precisely make up for these two shortcomings. First, by virtue of regret theory, an outranking relation on the comprehensive MSIS is constructed according to the regret-rejoicing index. Second, objects in the outranking relation are classified into three different domains by a clustering method. In each domain, the ranking of objects can be calculated by using the relative closeness coefficient. Finally, we use the cases in the database to simulate the experiment to verify the decision-making effect of the proposed model. Comparative analysis and experimental analysis also show the effectiveness, superiority, and stability of the proposed model.

Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges.

A Multi-Objective Hybrid Genetic Algorithm for Sizing and Siting of Renewable Distributed Generation

Renewable generation has been addressed in several aspects but it still represents a new paradigm for the expansion of the electricity supply. This paper aims to propose a new model for the sizing and siting problem of distributed generation (DG), based on renewable sources and considering three main aspects: technical, from the distribution utility viewpoint; economical, from the DG owner’s viewpoint, and environmental, from a sustainability perspective. A multi-objective Genetic Algorithm and the Maximin metric are implemented to obtain optimal Pareto sets; also, three decision criteria, considering the concept of preference, are applied to select a final solution from Pareto sets. Case-studies are carried out in medium voltage systems: the 69-bus distribution test system, known from literature, and a 918-bus Brazilian distribution system. Diversity of alternatives in the obtained Pareto sets testify algorithm effectiveness in searching for solutions to the distributed generation sizing and siting problem, in order to ensure power loss reductions, investment return, and environmental benefits. The proposed methodology contributes to the discussions and perspectives among electricity utilities, DG owners, society, and regulators regarding planning and decision making tools.

Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging

Utilization of fast surrogate models has become a viable alternative to direct handling of full-wave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques are severely affected by the curse of dimensionality. This is a serious limitation when it comes to modeling of highly nonlinear antenna characteristics. In practice, general-purpose surrogates can be rendered for the structures described by a few parameters within limited ranges thereof, which is grossly insufficient from the utility point of view. This paper proposes a novel modeling approach involving variable-fidelity EM simulations incorporated into the recently reported nested kriging modeling framework. Combining the information contained in the densely sampled low- and sparsely sampled high-fidelity models is realized using co-kriging. The resulting surrogate exhibits the predictive power comparable to the model constructed using exclusively high-fidelity data while offering significantly reduced setup cost. The advantages over conventional surrogates are pronounced even further. The presented modeling procedure is demonstrated using two antenna examples and further validated through the application case studies.

Optimal scheduling of PHEVs and D‐BESSs in the presence of DGs in a distribution system

Optimisation of cost and load flattening for a distribution network is attempted in this work. The objective function is described in terms of energy cost, C O 2 emissions, real power losses, and load flattening. The solution is envisaged in terms of hourly scheduling of distributed generations (DGs), distributed battery energy storage systems (D-BESSs), and plug-in hybrid electric vehicles (PHEVs). An investigation in the reformulation of the cost of energy is carried out to eliminate the solutions involving excessive charging and discharging of BESSs/D-BESSs and PHEVs. It is demonstrated that simultaneous optimisation of cost, C O 2 emissions, real power losses, and load flattening cannot be effectively solved as a weighted sum objective function. An e -constraint method is applied to obtain the optimal scheduling to achieve cost optimisation, load flattening, and minimisation of C O 2 emissions from the utility point of view. A case of decentralised multi-agent optimisation problem is also formulated and compared. It is observed that the combination of the scheduling of DGs, BESSs/D-BESSs, grid-to-vehicle/vehicle-to-grid can successfully be used to significantly reduce the system peak demand along with system cost, losses and C O 2 emissions.

A peak-load-reduction-based procedure to manage distribution network expansion by applying process-oriented costing of incoming components

Peak load reduction (PLR) is one of the applied strategies in demand response (DR) program to manage the costs of an electric distribution utility. Besides, this strategy can affect the costs of incoming new components (INC) from the utility viewpoint in the expansion phase, which consists of the processes of design, purchase, installation, and operation. Accordingly, considering these processes, this paper addresses a process-cost-oriented model seeing the PLR program to decide about the optimal investment value of network expansion. In the new paradigm, the costs of each process are identified, and the effect of PLR on these costs is analyzed. Moreover, to make optimal decisions, variations of the overall process costs and PLR program cost are investigated. A real case study is also provided to evaluate the capability of PLR using the proposed model. The results reveal that the overall cost is reduced by about 18%, due to the 5.7% reduction in the peak load.

Equilibrium in Ethic Economics

We will study the concept of equilibrium in conventional and ethic economics in this paper. By a general review of the subject of equilibrium from basic sciences' point of view, we will study the meaning of equilibrium at different levels of micro, macro, and international economics; and by considering the lust and anger powers of human being, the concept of optimizing human behavior in Neoclassical theory will be studied. The hypothesis of “rational behavior” and philosophical and the root of thoughts and human behavior modeling in neoclassical economics will be analyzed from pleasure or utilitarianism-based point of view. By putting forward the concept of “perfection” as materializing innate power of creatures, we introduce the concept of ethic science so that we will review the correctness and goodness of actions and qualities of the human being in the process of optimizing economic behavior. Level of equilibrium in the powers as prescribed by ethic science with the meaning of preventing overindulgence and under-indulgence will be discussed. The meaning of equilibrium in ethic economics is a global optimum and in the form of utility point of view, has a broader domain of qualities and intellectualities and human being spirituals always at least is in a position that is better than Neoclassical optimized behavior (which is a local optimum).Some qualities related to economic behavior and overindulgence and under-indulgence and their equilibrium have also been considered. Equilibrium in ethic economics means using resources and locating everything in its right position and in the direction of obtaining human being perfection. Putting things in their right position is the optimal use of them from a mathematical point of view, and perfection is defined as reaching the ultimate innate of every creature. This means that in order to maximize the utility, resources should be used in a manner that in addition to ensuring human being material needs, assure the necessary background for maximizing mental and spiritual growth and elevation of him.
 DOI: https://doi.org/10.5281/zenodo.3402335

Rheological and thermal properties of mixtures of hydroxyl-terminated polybutadiene and plasticizer (Rapid communication)

Mixtures of hydroxyl-terminated polybutadiene (HTPB) and dioctyladipate (DOA) as a plasticizer, which after crosslinking are applied as binders in heterogeneous propellants, were studied.The influence of mixture composition on rheological and thermal properties, important from technological and utility viewpoint were specified. The temperature dependence of prepared mixtures viscosity were studied. Systems were subjected to crosslinking and values of pot life (tpl) were determined. It was stated that tpl rose with increasing plasticizer content. Differential scanning calorimetry and thermogravimetry techniques were used toanalyze thermal stability of mixtures. It was concluded that applied component scould not decompose in the temperature range of 290–350 K and studied mixtures did not cause the hazard of thermal explosion.

Analysis and modeling of the effects of process parameters on specific cutting energy in abrasive water jet cutting

The problem of cutting difficult-to-machine materials used in the aerospace industry, aircraft industry, and automobile industry, led to the development and application one of today?s most attractive technology for contour cutting - abrasive water jet cutting. For the efficient use of abrasive water jet cutting, it is of great importance to analyze the impact of process parameters on performance indicators, such as cutting quality, productivity, and costs. But also, from the energy utilization point of view, it is very important to analyze the impact of these parameters on the specific cutting energy which represents the amount of energy spent on the removal of material in the unit time. Having this in mind, this study presents the experimental results of abrasive water jet cutting of aluminum alloy with the aim of creating a mathematical model for estimating specific cutting energy as an important indicator of the degree of utilization of the available energy in the cutting process. The mathematical model of the specific cutting energy is explicitly represented as a non-linear function of the process parameters, obtained by the artificial neural network.

Comparative study of coal combustion residues from pulp and paper mills of Assam

ABSTRACTIn the present work, the physicochemical, mineralogical, and morphological characteristics of coal combustion residues (CCRs) collected from two different Pulp and Paper Mills of Assam, India, have been investigated. CCRs from both the sources were mechanically sieved to obtain various size-classified fractions and their physical properties were determined using standard methods. X-ray diffraction (XRD), Fourier Transformation Infrared (FTIR) Spectroscopy, Scanning Electron Microscopy (SEM) etc. techniques were employed to study the mineralogical and morphological characteristics of each size classified fraction. The loss on ignition (LOI) values of the coarser fractions were found to be unexceptionally high, implying the presence of a huge amount of unburned carbon, and indicating the incomplete combustion of feed coal. From the utilization point of view, coarser fractions may be recycled (as domestic fuels) and less-coarse fractions may be used as adsorbents of toxic organic chemicals. Due to the larger water-holding capacities (WHCs), the coarser fractions may be used for soil amendment.

Changes in sub-soil river water quality upon its open storage-a case study.

A study was carried out to investigate the changes in the physicochemical and biological properties of sub-soil river water upon its storage in a man-made reservoir. Palar sub-soil and reservoir water samples were collated fortnightly for a period of 5years (2010-2014). The open reservoir is used as a reliable raw water source for condenser cooling systems and for the demineralizing (DM) plant input of Fast Breeder Test Reactor (FBTR), Madras Atomic Power Station (MAPS), and other laboratories at Kalpakkam, southeast coast of India. Relatively high nutrient concentration was observed in the Palar sub-soil water, and a significant reduction in average concentration (μmoll-1) of phosphate (Palar 1.92; open reservoir 1.54) and nitrate (Palar 9.78; open reservoir 5.67) was observed from Palar to open reservoir. Substantial increase in pH (Palar 8.05; open reservoir 8.45), dissolved oxygen (mgl-1) (Palar 6.07; open reservoir 8.47), and chlorophyll-a (mg m-3) (Palar 1.66; open reservoir 8.43) values were noticed from the Palar sub-soil water to open reservoir water. It is concluded that sub-soil water with higher nutrient concentrations when stored openly, exposing to the sun, resulted in growth of plants, planktonic, and macrophytes, which led to substantial deterioration in water quality from its utility point of view as a condenser cooling medium and raw water input for DM plant.

Prioritization of Corrective Actions from Utility Viewpoint in FMEA Application

Failure mode and effects analysis has been extensively used as a powerful method in a wide range of industries, but many scholars questioned the risk priority number method and proposed some new methods to improve. However, these methods still only evaluated from risks viewpoint while ignoring the effectiveness of corrective actions from utility viewpoint. In practical, it may not reach significant corrective effectiveness because of the corrective efficiency if corrective action is ignored. In addition, corrective actions may be treated as a complex system; they may not be simple and have an independent relationship with each other; the interdependence relationship; and the sequence or structure of hierarchy; even feedback relationship may exist. This study develops a fuzzy interpretive structural model in order to evaluate the structure of hierarchy and interdependence of corrective actions, and integrating the analytic network process with decision‐making and trial evaluation laboratory to take account into the causal relationship and influence strength of corrective actions to obtain the more accuracy weights. At last, a case study implemented to demonstrate that the proposed approach effectively circumvents the drawbacks of traditional risk priority number method and adapts flexibly to real‐world situations. Copyright © 2016 John Wiley & Sons, Ltd.

ANALYSIS OF INFILL FRAME WITH GAP ELEMENTS USING FINITE ELEMENT APPROACH

The rapid urbanisation demands the need of high raised buildings which are always vulnerable to the lateral loads caused due to natural calamities. These lateral loads affect the stability of the structure. The shear walls, which are provided to resist the lateral forces, are not desirable from utility point of view as they come in the way of vehicular movement in the parking floor. In this context the contribution available from wall panels, called infill walls is considered. In this paper, the contribution offered from infill walls to the lateral strength of the building is evaluated using FEM approach. In this approach the infill wall contribution is replaced with two diagonal struts joining the opposite corners of the frame. The general purpose Finite Element package MSC NASTRAN is used to evaluate the infill contribution. Frames with different aspect ratios of span to height with and without wall opening are taken up for the study. On obtaining the strain energy of the infill frame, the infill wall is replaced by equivalent diagonal struts joining the opposite corners of the frame of width to match in strain energy. To make the application more widely applicable, the data obtained from different case studies has been tabulated to train a neural net. The train neural net is expected to offer the width of equivalent strut once the necessary input data is fed. The utility of the study is improved as more data is added.. Later the effect of crack widening in the infill panel was shown by the introduction of gap elements wherever the tensile stress was found more than the permissible value. The failure pattern when a horizontal load, vertical load and rotation each applied in turn at each corner of the infill panel with gap elements is studied

System Analysis of Multi-Criteria Optimization Methods on a Finite Set of Alternatives

The functions used by different optimization methods are interpreted with expected utility viewpoint. It makes possible to distinguish two groups of methods - criterion and functional choice ones. The first group of methods sets preferences on the values of the criteria, and the second - on the values of the functions presenting the preferences of decision maker on the scales of attributes. Such an interpretation of functions that does not depend on how they are created, allowed considering methods of multi-criteria optimization and multi-dimensional utility from unified positions. The analytic hierarchy process uses the priority function calculated based on the matrix of pairwise comparisons. So, it is related to the group of methods of functional choice too. The resulting system allows one to compare their methods for quality and evaluate the effectiveness of tasks solving.

ANALYSIS OF INFILL FRAMES USING NEURAL NETWORKS

High raised buildings are vulnerable to the lateral loads caused during natural calamities like earthquakes and cyclones. Lateral loads always affect the stability of structures. The shear walls, which are provided to resist these lateral forces, are often considered undesirable from utility point of view as they come in the way of vehicular movement in the parking area. Methods to evaluate the lateral strength from infill wall panels are studied here. In this paper, the contribution offered from infill walls to the lateral strength of the building is evaluated using a combination of FEM approach and Neural Networks. Since the integral action of the wall panels with the bounding frame is considered in this approach, the frame is called as infill frame. In the study the infill wall contribution is replaced using two diagonal struts joining the opposite corners of the frame. The Finite Element package MSC Nastran is used to evaluate the infill contribution. Frames with different aspect ratios of span to height, with and without wall openings are analysed. The strain energy of the infill frame is equated to the strain energy of frame with diagonal struts, from which the width of the equivalent struts is obtained. The equivalent diagonal struts are provided joining the opposite corners of the frame. In the present study the non linear behaviour of concrete has also been taken into consideration. To make the method more widely applicable, a large data bank with varying parameters of span/depth, beam/column sections, with and without infill openings and different grades of concrete is generated which shall be used for training a BOPN based neural net paradigm. The trained neural net is expected to furnish the width of equivalent strut, which can readily be used in the structural analysis of framed buildings. The utility of the study enhances as more training patterns are added to the neural net.

Two substitutable perishable product disaster inventory systems

A disaster inventory system is considered in which two substitutable items are stored for disaster management. In the event of disaster management, a particular product may become stock-out and the situation warrants that a demand for the particular product during its stock-out period may be substituted with another available similar product in the inventory. From the utility point of view, continuous review inventory models are quite appropriate in disaster inventory management. In this paper, a continuous review two substitutable perishable product disaster inventory model is proposed and analyzed. Since the inventory is maintained for disaster management, an adjustable joint reordering policy for replenishment is adopted. There is no lead time and the replenishment is instantaneous. For this model, some measures of system performance are obtained. The stationary behavior of the model is also considered. Numerical examples are also provided to illustrate the results obtained.

Stochastic Economic Load Dispatch with Multiple Fuels using Improved Particle Swarm Optimization

In this paper, Stochastic Economic Load Dispatch (ELD) problem with multiple fuels is solved using Improved Particle Swarm Optimization (IPSO). Generally, ELD problem is solved using deterministic models, but data required for such studies are rarely available with complete certainty. So uncertainties in unit’s generation, load demand and cost coefficients should be considered to get actual scenario. Thus, stochastic model for ELD problems is more suitable than deterministic model from the utilities point of view. ELD problem with deterministic model is first solved using IPSO to examine the effectiveness of the proposed method. Then IPSO is applied for ELD problem with stochastic model to investigate the real generation cost.