Types Of Tariffs Research Articles

Agricultural Trade Liberalisation in the 21st Century: Has It Done the Business?

AbstractBased on a novel, detailed, time‐consistent tariff database taking account of import protection developments in the agricultural sector since 2001, we propose a statistical decomposition of the changes in the various types of tariffs. The results show that the multilateral system has played a limited role in trade liberalisation over the period. Many countries have continued to apply much lower tariffs on agricultural products than their WTO ceilings. Moreover, there has been substantial unilateral dismantling of tariffs over the period, so that much of the liberalisation took place outside WTO and regional agreements. The number of regional trade agreements has surged, but their impact on applied agricultural tariffs has been limited. Finally, we investigate the tariffs, trade and production implications for food and agricultural products of two extreme scenarios in the future development of trade negotiations: an ambitious surge of regional agreements and a trade war within the WTO context.

АНАЛИЗ ЗАРУБЕЖНОГО ОПЫТА РАЗВИТИЯ КОНКУРЕНЦИИ НА РОЗНИЧНОМ РЫНКЕ ЭЛЕКТРИЧЕСКОЙ ЭНЕРГИИ

Promotion of competition at retail electricity markets and electric power industry liberalization are the worldwide trends. The rewarding experience of retail electricity markets performance demonstrates that the deregulated model of wholesale and retail electricity markets provides mostfavorite competitive mechanism. The UK and Northern Europe countries (Norway, Sweden, Finland, Denmark) competitive mechanisms practiced at retail electricity markets have analysed. The deregulated model of wholesale and retail electricity markets distinctive features has determined, also the applied types of electricity supply contract and tariffs, the special aspects of electric power pricing for ultimate customers have perceived.

Economic analysis of the energy consumption of a vending machine in a Mexican university building

Food, water, snack, and soda vending machines have recently become more abundant in non-residential buildings. This increase in the number of vending machines directly affects the electricity consumption of the building where they are installed. The number of vending machines is directly related to energy consumption and influences the total electrical bill of the entire building. We present a case study of a non-residential building that is designated as a university level educational facility. Within this analysis we realize a comparison between the three energy costs that are related to the three different tariff types in Mexico. We conduct an analysis of the behavior of the electrical load that the vending machine represents, which is focused on reviewing two objectives: the hours of operation according to the electrical tariff that is applied and the incidence of loads in relation to energy consumption (kWh) and electrical potential (kW) in the electrical network of the building. The results shown in this article are a great help when making decisions such as the number of vending machines to install according to the economic aspect and the electricity tariff contracted.

Tariffs and Carbon Emissions

ABSTRACTInternational trade and the environment are uneasy partners. Both environmentalists and free traders worry that the pursuit of one goal may obstruct the other. Nowhere is this tension more evident than in the area of climate change. Does trade liberalization increase carbon emissions? Do efforts to reduce carbon emissions lead to protectionist pressures? This paper addresses these questions by examining the relationship between CO2 emissions and tariffs in 109 to 153 countries from 1988 to 2013. Using instrumental-variable regressions to address reciprocal causation, I find that emissions reductions led to higher tariffs on manufactured goods. This suggests that carbon-intensive industries responded to carbon restrictions by lobbying against trade liberalization. In contrast, emissions did not affect tariffs on less carbon-intensive primary products, and neither type of tariff affected CO2 emissions. My results imply that efforts to combat climate change may obstruct trade liberalization, but the latter should not hinder climate change mitigation.

Back to 1913?: The Ryan Blueprint and Its Problems

With the election of Donald Trump and the Republican Party’s domination of Congress, it is time to seriously consider President Trump’s tax plan and House Speaker Paul Ryan’s blueprint for fundamental tax reform. The Trump plan lacks detail, but includes unrealistically large and regressive tax cuts. The Ryan blueprint combines reduced individual rates with a consumption or cash flow type business tax applicable to large businesses. This blueprint represents a regressive return to the type of tariffs that financed the US government before the passage of the Sixteenth Amendment in 1913, which is a betrayal of the working class voters that elected Mr. Trump. In addition, the Ryan blueprint has three major problems: It is incompatible with our WTO obligations and with our tax treaties, and will not solve the problems of income shifting and inversions it is designed to address.

Online scheduling of plug-in vehicles in dynamic pricing schemes

In recent years there has been an increase in the use of plug-in electric vehicles (PEVs). Though it has many advantages, PEVs could stress the grid if their charging schedule is not managed properly. There are several issues to be addressed such as (i) Scheduling of PEV under different types of Tariffs (ii) Prediction of load profile and charging requirement. This paper presents three algorithms for scheduling PEV charging by an aggregator under different conditions. This paper has an aim to present the approaches for different possible cases to schedule PEVs charging. In order to achieve this ambition, first, a simple placement algorithm to schedule the PEVs is developed provided prices are predetermined. Then the scheduling problem is formulated as a single stage decision making problem in case prices are not known in advance and PEVS are independent atomic loads. However, it has been researched that PEVs are independent non-atomic loads. Finally, this paper modifies other cases and then the problem is formulated as a multistage decision making problem to determine the optimum schedule in more realistic scenario. In all cases, proposed algorithms are simulated for a building with an objective to schedule PEVs charging during working hours such that the total cost of energy is minimized and the requirements of user are also satisfied.

Transmission and generation investment in electricity markets: The effects of market splitting and network fee regimes

We propose an equilibrium model that allows to analyze the long-run impact of the electricity market design on transmission line expansion by the regulator and investment in generation capacity by private firms in liberalized electricity markets. The model incorporates investment decisions of the transmission system operator and private firms in expectation of an energy-only market and cost-based redispatch. In different specifications we consider the cases of one vs. multiple price zones (market splitting) and analyze different approaches to recover network cost—in particular lump sum, generation capacity based, and energy based fees. In order to compare the outcomes of our multilevel market model with a first best benchmark, we also solve the corresponding integrated planner problem. Using two test networks we illustrate that energy-only markets can lead to suboptimal locational decisions for generation capacity and thus imply excessive network expansion. Market splitting heals these problems only partially. These results are valid for all considered types of network tariffs, although investment slightly differs across those regimes.

Cost Reduction Ability by Electricity Tariff Selection for Construction Facilities Located in Non-price Areas

State of the art in the tariff type selection in the retail and the wholesale electricity market for construction or reconstruction facilities located at Far East are considered. As a management solution the electricity tariff’s selection for enterprises at stage of construction or reconstruction is accented.

Effect of tariffs on the performance and economic benefits of PV-coupled battery systems

The use of batteries in combination with PV systems in single homes is expected to become a widely applied energy storage solution. Since PV system cost is decreasing and the electricity market is constantly evolving there is marked interest in understanding the performance and economic benefits of adding battery systems to PV generation under different retail tariffs. The performance of lead-acid (PbA) and lithium-ion (Li-ion) battery systems in combination with PV generation for a single home in Switzerland is studied using a time-dependant analysis. Firstly, the economic benefits of the two battery types are analysed for three different types of tariffs, i.e. a dynamic tariff based on the wholesale market (one price per hour for every day of the year), a flat rate and time-of-use tariff with two periods. Secondly, the reduction of battery capacity and annual discharge throughout the battery lifetime are simulated for PbA and Li-ion batteries. It was found that despite the levelised value of battery systems reaches up to 28% higher values with the dynamic tariff compared to the flat rate tariff, the levelised cost increases by 94% for the dynamic tariff, resulting in lower profitability. The main reason for this is the reduction of equivalent full cycles performed with by battery systems with the dynamic tariff. Economic benefits also depend on the regulatory context and Li-ion battery systems were able to achieve internal rate of return (IRR) up to 0.8% and 4.3% in the region of Jura (Switzerland) and Germany due to higher retail electricity prices (0.25CHF/kWh and 0.35CHF/kWh respectively) compared to Geneva (0.22CHF/kWh) where the maximum IRR was equal to −0.2%.

Assessment of electricity price uncertainty impact on the operation of multi‐carrier energy systems

Today, there are serious trends to use all potentials of the available energy carriers through the concept of energy hubs. However, different types of inherent uncertainties in these systems are the main challenge for utilisation of energy hubs. Furthermore, a framework is presented to analyse the multi-carrier energy systems under five zones of uncertainty in order to achieve the maximum electricity profits. For example, it is shown that the profit of the system is <8.5% despite the 50% of uncertainty in the state without combined heat and power (CHP) while system earns a profit of at least 12.8 in the state with CHP. The Monte Carlo simulation method has used to generate different scenarios. The proposed design methodology decides on which model is suitable for hub. It includes detailed models for transducer performance and hub using the mean and variance of profits and assess of their impact individually. The model also considers information on energy products used as per-unit form. Price and electricity markets have intended as in the day-ahead and real-time pricing with three types of tariffs during the day.

Power-use profile analysis of non-domestic consumers for electricity tariff switching

For both domestic and non-domestic consumers, dynamic electricity tariffs have been proposed as a way to reduce their energy costs and to facilitate demand-side response. It is difficult for businesses which are tenants to adopt energy efficiency measures; thus, tariff switching is the easier option. Therefore, understanding the limits of the cost saving offered by tariff switching is an important step. This raises two questions: by how much could bills be reduced, and would all consumers benefit equally? Using a dataset of half-hourly electricity readings from more than 7500 British businesses, we performed an empirical analysis to discover which types of businesses might have lower or higher costs when changing between static and real-time tariffs. We identified differences in demand profiles that demonstrate that the decision whether to switch tariff types is a subtle one which may have a significant cost impact. The dataset was aggregated into five categories: Entertainment, Industry, Retail, Social, and Other. Our analytical methods can be used to distinguish the differences between typical electricity demand profiles for small- to medium-sized businesses and sectors in different market options. Our analyses of switching to a real-time tariff suggest that most of those small- to medium-sized businesses that would reduce their annual electricity bill would gain by no more than 10 %. Most of these businesses would gain by less than 5 %. This, we suggest, sets a realistic upper limit of the likely cash savings before energy efficiency, or other measures must be taken to further reduce bills.

Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

To match supply and demand, shifting of load from peak period to off-peak period is one of the effective solutions. Presently flat rate tariff is used in major part of the world. This type of tariff doesn’t give incentives to the customers if they use electrical energy during off-peak period. If real time pricing (RTP) tariff is used, consumers can be encouraged to use energy during off-peak period. Due to advancement in information and communication technology, two-way communications is possible between consumers and utility. To implement this technique in smart grid, home energy controller (HEC), smart meters, home area network (HAN) and communication link between consumers and utility are required. HEC interacts automatically by running an algorithm to find optimal energy consumption schedule for each consumer. However, all the consumers are not allowed to shift their load simultaneously during off-peak period to avoid rebound peak condition. Peak to average ratio (PAR) is considered while carrying out minimization problem. Linear programming problem (LPP) method is used for minimization. The simulation results of this work show the effectiveness of the minimization method adopted. The hardware work is in progress and the program based on the method described here will be made to solve real problem.

The strength of the waterbed effect depends on tariff type

We show that the waterbed effect, i.e. the pass-through of a change in one price of a firm to its other prices, is much stronger if the latter include subscription rather than only usage fees. In particular, in mobile network competition with a fixed number of customers, the waterbed effect is full under two-part tariffs, while it is only partial under linear tariffs.

Predicting winning and losing businesses when changing electricity tariffs

By using smart meters, more data about how businesses use energy is becoming available to energy retailers (providers). This is enabling innovation in the structure and type of tariffs on offer in the energy market. We have applied Artificial Neural Networks, Support Vector Machines, and Naive Bayesian Classifiers to a data set of the electrical power use by 12,000 businesses (in 44 sectors) to investigate predicting which businesses will gain or lose by switching between tariffs (a two-classes problem). We have used only three features of each company: their business sector, load profile category, and mean power use. We are particularly interested in the switch between a static tariff (fixed price or time-of-use) and a dynamic tariff (half-hourly pricing). We have extended the two-classes problem to include a price elasticity factor (a three-classes problem). We show how the classification error for the two- and three-classes problems varies with the amount of available data. Furthermore, we used Ordinary Least Squares and Support Vector Regression models to compute the exact values of the amount gained or lost by a business if it switched tariff types. Our analysis suggests that the machine learning classifiers required less data to reach useful performance levels than the regression models.

Antecedents of international mobile Internet tariff type preferences : an empirical study of roaming customers

Purpose– International roaming (IR) makes it possible to conveniently use mobile communication services (MCS) such as MI access abroad without switching providers, devices or subscriber identity module (SIM) cards. To increase the intensity of competition in the intra-European Union market for IR services, customers will be enabled to buy IR voice and MI access services separately from their existing domestic MCS, as of July, 2014. Specifically, for separated international MI services providers can choose from three different charge types (use-dependent, flat and combination of flat and use-dependent). The purpose of this paper is to empirically examine customer preferences regarding these tariff types for separated international MI services.Design/methodology/approach– Six research questions concerning antecedents of tariff type preferences for separated international MI access services are derived from a literature review. They are empirically addressed by analyzing survey responses obtained for a sample of 496 German-speaking MCS users.Findings– Customers who actively seek for IR price information, consider IR services to be useful, exhibit high use intensities of MI services, do not restrict their MI usage when travelling abroad and tend to prefer flat rates to other pricing schemes. In contrast to these rather “active users”, customers favoring strictly use-dependent tariff plans exhibit significantly lower IR price information seeking efforts and comparatively low use intensities of MI services. Pricing schemes with MI allowances are especially liked by customers who are well-informed regarding and satisfied with IR prices, report above average use intensities of MI services, restrict their MI use abroad, are more likely to switch providers and use MCS mainly for job-related purposes.Research limitations/implications– The study is based on a German-speaking sample, which deviates from the German adult population. Additionally, the analysis is limited to stated instead of behaviorally revealed preferences for cross-border MI tariff types. Price thresholds influencing whether a cross-border MI tariff is entered into a consumer’s relevant set of offerings are not examined.Practical implications– The research suggests that mobile network operators are well-advised to offer a clearly structured menu of a limited number of tariffs directed to the three profiled customer segments. Notwithstanding the advantages of such a set of rate plans, international MI tariff schemes with a data volume allowance appear to be generally beneficial both from a provider and an end-customer perspective.Originality/value– To date, little is known about customer preferences concerning the three rate plan categories and on antecedents of such preferences in the field of MI access abroad. The present study takes a first step to narrowing this knowledge gap.

Demand response for residential buildings based on dynamic price of electricity

In the U.S., heating, ventilating and air conditioning (HVAC) systems are the largest consumers of electrical energy and a major contributor to peak demand. To reduce both peak load and energy cost, the set-point temperature of HVAC can be controlled depending on the electricity price. This paper presents a proposed controller that curtails peak load as well as saves electricity cost while maintaining reasonable thermal comfort. The controller changes set-point temperature when the retail price is higher than customers preset price. To evaluate the performance of the newly developed demand response controller, detailed energy models for two residential buildings are developed to analyze HVAC power consumption for different house sizes and floor plans. The house models are assumed to be located in Austin, Texas, USA and generated with OpenStudio and EnergyPlus. The design of internal load and occupation schedule are based on a residential energy consumption survey and experimental data by the Pecan Street Project, Austin, TX. In addition, historical data from Austin Energy for residential customers, 2012 is used to calibrate two house models. In addition, this paper uses the historical real-time wholesale price data for the Electricity Reliability Council of Texas (ERCOT) wholesale electricity market to model the two types of real-time tariffs that many utilities in the U.S. currently use to generate dynamic pricing for demand response programs. The simulation results show that our demand response controller could provide up to 10.8% of energy cost savings by using the proposed controller with dynamic pricing. While avoiding significant discomfort due to temperature change. Also, the results present potential for saving considering peak load by 24.7% and total electrical energy saving for HVAC in homes by 4.3% annually.

The Strength of the Waterbed Effect Depends on Tariff Type

We show that the waterbed effect, i.e. the pass-through of a change in one price of a firm to its other prices, is much stronger if the latter include subscription rather than only usage fees. In particular, in mobile network competition with a fixed number of customers, the waterbed effect is full under two-part tariffs, while it is only partial under linear tariffs.

Time of Use Tariff Design for Domestic Customers from Flat Rate by Model-based Clustering

This paper proposes a novel method to design feasible Time-of-Use (TOU) tariffs from flat rate by clustering techniques for domestic customers. The determinations in two groups of TOU are identified following variation in energy prices and in demand respectively. With a number of price-oriented and load-oriented TOU tariffs, the investigation is further carried out to explore the effects of different types of TOU tariffs on domestic demand response (DR). The DR in this paper is enabled by a household storage battery for benefit quantification, and the objective of the DR to each specific TOU tariff is to minimize the electricity bills for end customers.

The Problems Related to Renewable Energy: The Italian Case

The present work has the task of developing a create an analysis of the main problems related to the development of renewable energy in relation to the events in Italy. We take into account the various types of tariffs, avoid concentrations of plants and long transports biomass, stop generating facilities discomfort, stop the drastic dedicated to energy crops, survey.

A Comparative Study of Renewable Energy Industry Regulation on Feed-In Tariffs Based on Pricing Strategy of Value Standard Method

Based on pricing strategy of value standard method, we establish a three-stage game model of energy production to compare the differences of optimal regulated price and social welfare under three regulation types of feed-in tariffs. We show that the optimal price levels under three main regulation types are different. But the choice of regulation type does not impact the optimal social welfare. So policymakers with different preferences may make regulation decisions in different ways. This successfully explains why many regulation types exist in different countries. Moreover, although it is difficult to determine the optimal price by the value standard method in practice, the conclusions of this paper also provide a judgment criterion for other pricing strategies on how to choose a suboptimal regulation type.