Tariff Model Research Articles

Socioeconomic impact of Brazilian electricity market liberalization: Forecasting and optimized tariff analysis

–This article integrates forecasting methods with an optimized tariff model to assess the effectiveness of the schedule proposed by the Brazilian Association of Energy Traders, as outlined in the technical note NT n°10/2022-SRM/ANEEL. This note discusses the regulatory measures to fully open the free energy market to all captive consumers by 2026. Several models, including Winters, SARIMA, ARIMA, and trend analysis were compared to determine the most suitable method for each input variable in the TAROT model, aiming to enhance forecasting accuracy. The results show that the new schedule proposed in the technical note successfully maintains the balance between the economic surplus of concessionaires and the socioeconomic welfare. Despite both approaches declining during the migration period of low-voltage consumers, their surpluses remain positive. However, there are negative effects on tariffs, impacting all consumer groups remaining in the regulated market, both high-voltage and low-voltage consumers. A key conclusion is that further regulatory changes are essential to mitigate additional increases in energy tariffs, aligning the proposed schedule with the reduction of legacy contracts.

Geospatially Informed Water Pricing for Sustainability: A Mixed Methods Approach to the Increasing Block Tariff Model for Groundwater Management in Arid Regions of Northwest Bangladesh

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges.

항만당국과 터미널 운영사 간 임대 계약 방식의 성과에 관한 연구

This study examines the performance of port authorities and terminal operators under different types of concession contracts in ports. The port authority signs into a concession contract with the terminal operator to receive fee, and the operator utilizes the terminal to provide loading and unloading services. The demand at the port is affected by the terminal operator's price and service level. This study analyzes the performance of each model using game theory under three different concession schemes: two-part tariff model, revenue-sharing model, and revenue-cost-sharing model. The results show that the revenue-sharing model can improve the profitability of port authorities and terminal operators compared to the two-part tariff model, but it may result in lower service levels at the terminal. On the other hand, the revenue-cost-sharing model can improve both the profit and the service level of each party compared to the two-part tariff model, and can achieve higher performance than the revenue- sharing mode. The significance of this study is that it analyzes the revenue sharing model, which has not been studied much in the past, and considers the service level in analyzing the effect of concession contracts.

Holistic regulatory framework for distributed generation based on multi-objective optimization

Regulatory changes associated with distributed generation have occurred in several countries (e.g., the USA, Germany, the UK, and Australia). However, there is a lack of robust and holistic analytical models that can be used to implement the best regulatory framework among possible options. In this context, the present paper proposes a cutting-edge regulatory framework for distributed generation based on multi-objective optimization, taking into account socioeconomic (socioeconomic welfare created by the regulated electricity market and electricity tariff affordability) and environmental (global warming potential) indicators. Such indicators are modeled primarily based on the optimized tariff model (socioeconomic regulated electricity market model), Bass diffusion model (forecasting model of distributed generation deployment), and life cycle assessment (environmental impact assessment method). The design variables are assumed to be the regulated electricity tariff and remuneration of the electricity injected into the grid over the years. First, the proposed methodology is applied to fifteen large-scale Brazilian concession areas with a significant deployment of distributed generation assuming two approaches, a multi-compensation scenario, where the compensation is set individually for each concession area, and a single-compensation scenario, where the compensation is set equally for all concession areas. Then, the optimal solutions are compared to Ordinary Law 14300, which is a recently implemented regulatory framework for distributed generation in Brazil. Results demonstrate that Ordinary Law 14300 is a dominated or non-optimal solution since it is not located on the optimal Pareto frontiers for any of the assessed concession areas. Assuming the Euclidian knee points, benefits averaging 33% and 15% were achieved in terms of electricity tariff affordability for the multi and single-compensation scenarios, respectively, with small losses of 8% and 3% in terms of socioeconomic welfare and global warming potential. Though the proposed methodology is applied in the Brazilian context, it can also be applied to other countries with regulated electricity markets; thus, it is expected to be valuable for researchers, government institutions, and regulatory agencies worldwide.

Dual-channel decision models for the transnational supply chain considering strategic inputs and compensation

Based on a transnational dual-channel supply chain consisting of the domestic manufacturer and retailer, this paper constructs four models, namely, the without tariff model, the tariff model, the retailer’s strategic inputs model, and the manufacturer’s compensation model, to investigate the impact of the tariff imposing on supply chain decisions, the effect of the retailer’s strategic inputs to hedge against tariffs, and the incentive effect of the manufacturer’s compensation. The results show that the tariff imposed by the foreign government leads to higher product prices and lower sales volumes, resulting in welfare losses for foreign consumers. When the domestic retailer makes strategic inputs, the prices of products in the foreign market decrease and the sales volumes increase, which increases the profits of the domestic retailer and manufacturer and improves the welfare of foreign consumers. The equilibrium solutions of the models also show that the manufacturer has an incentive to compensate the retailer for its strategic inputs; when the manufacturer compensates for the retailer’s strategic inputs, the profit of the retailer and the manufacturer will be improved again, and thus, the whole supply chain will achieve Pareto improvement.

Sustainable Water Service Tariff Model for Integrated Watershed Management: A Case Study in the Ecuadorian Andes

This study addresses the financial sustainability challenge of integrated watershed management (IWM) in regions with inadequate water service tariffs. A novel water service tariff model is proposed, incorporating supply costs, water loss reduction investments, and IWM expenses informed by user perceptions. The model is applied to an intermediate Andean city in southern Ecuador, where the current tariff impedes the financial viability of the water utility, reflecting a regional trend. The results indicate a necessary tariff increase exceeding 100% to cover the costs and support IWM. The economic value of watershed environmental services (WES) were estimated at USD 1,505,530.64 per year. This value translates to an average water consumption of 20 m3/user/month, equivalent to a WES of USD 2.60 per month. Despite the users’ willingness to pay falling below the estimated economic value of WES, there is a clear need for implementing incentive programs to promote water conservation and policy adjustments that favor the financial sustainability of water supply companies in developing countries.

The Impact of U.S. Carbon Tariff on Chinas Exports and Welfare Based on Empirical Analysis and Game Models

This paper will begin by formulating an optimal tariff model between China and the U.S., leading us to an equilibrium point. From this vantage point, we will deduce the consequences of U.S. tariffs on China's exports and the ramifications of U.S. carbon tariffs on China's societal welfare. Next, we will develop an economic model considering the existing China-U.S. tariffs and their trading relationship. This model will help determine the influence of U.S. tariffs on China's export volume and societal welfare. In addition, we will compute the impact of U.S. tariffs on China's societal welfare and export to the U.S., factoring in China's carbon emissions per 100 yuan of GDP, and finally, concern the industrial impact of such carbon tariffs. Third, using two distinct game models, we would probe into the viability and possibility of the U.S. levying a carbon tariff on Chinese exports. The evolutionary game models reflect real-world scenarios, which point out that the U.S. will eventually apply a carbon tariff on China. Next, the dynamic game model considers different parties, Chinas government and firms, and different factors, environmental costs, and green subsidies. The model provides the circumstances in which the U.S. will levy a carbon tariff, whether China should provide a green subsidy, and whether the company should implement green production technology. Finally, we would discuss potential strategies China might adopt to navigate the challenges of the U.S. carbon tariff and examine the broader implications of such a move.

Public-Transportation Credits: The potential of three-part tariffs in public transportation

In December 2023, public-transportation providers in Switzerland introduced Public-Transportation Credits (PTCs). PTCs are credits (or “allowances”) that are greater in amount than their price and can be used to purchase any type of public-transportation tickets within a year. With the initial fixed payment, the subsequent use of the allowance and the eventual return to the standard fare, PTCs represent three-part tariff models. We explore the potential of PTCs to target particularly elastic segments of the demand curve, simultaneously allowing for increased consumption and higher revenue. To assess the revenue impact of the PTC empirically, we analyze a pilot study conducted by the Swiss public-transportation providers. In a randomized field experiment with 200,000 PTC invitees and 911 actual PTC buyers, we use the dispach of invitations as an instrumental variable. While observing substantial revenue increases, this result is insignificant due to the weak relationship between invitees and buyers. Therefore, we complement our analysis with a selection-on-observable approach, utilizing machine-learning techniques to match PTC buyers to customers in the control group. This way, we reveal a highly significant treatment effect, indicating a revenue enhancement of CHF179.7 per PTC (approximately USD200). Leveraging our comprehensive dataset and insights from a non-buyer survey, we predict a demand of around 200,000 units for the market-launch version of the PTC.

Analysis of Hemodialisa (HD) Services Based on Comparison of Calculations Hospital Rates with Rates BPJS Kesehatan

For hospitals to grow and develop in order to be managed efficiently and effectively, it is necessary to face intense competition in the world of health services. If they want to survive in competition, hospitals need to recalculate their existing hospital rates, namely by using a competitive tariff model calculation. Based on the results of interviews with the head of the hemodialysis (HD) unit, it was stated that 95% of HD patients seeking treatment at Wangaya Hospital were BPJS patients and the rest were general patients. There is a difference in cost sharing between HD rates at hospitals and InaCBG's (BPJS) rates. Wangaya Hospital previously set a fee for HD patients at Rp. 990,000, while the BPJS has set a tariff for InaCBG's HD patients at IDR 887,100. Between HD rates from hospitals and BPJS, there is a difference in cost sharing. Researchers in this case only compared HD rates based on hospital rates and rates based on BPJS, so that the cost sharing value was small. So far, the hospital has never recalculated the difference based on these two rates. Based on this calculation, hospitals will incur losses in HD services in 2020, thus further research is needed on the topic above.

Day ahead demand response model with algorithm-based consumption classification and tariff planning

Demand Response (DR) programs effectively support the supply-demand balance in power systems. This study proposes a new Time-of-Use (ToU) tariff model, a type of price-based demand response (DR). The proposed model aims to shape the daily consumption profile of the distribution region by encouraging consumers through tariffs. Generally, in ToU demand response, various presumptions are being adopted to define consumption periods and consumer classes. It is unlikely that these presumptions are suitable for every day of the year and every consumer in the system. Achieving these definitions and classifications based on algorithms, free from human error, will increase the success and comprehensiveness of the DR program. To maximize success in this context, a deep learning model has been leveraged for day-ahead consumption forecasting. The forecasted daily consumption profile is partitioned into ToUs by using the Moving Boundary method. In addition, consumers within the region have been segmented based on the similarities in consumption behavior. Tariffs have been priced for each cluster through an optimization model that considers their participation rates in total consumption and contributions to consumption in ToU regions. The proposed model has been tested over a dataset belonging to a distribution system where different types of consumers coexist. Two sample days have been chosen as one is a weekday and the other is a weekend. The results prove that shifting consumption as encouraged by the proposed TOU method reduces consumers' costs. While, the profitability of the system operator is also preserved.

Multi-agent game operation of regional integrated energy system based on carbon emission flow

In the process of promoting energy green transformation, the optimization of regional integrated energy system faces many challenges such as cooperative management, energy saving and emission reduction, as well as uncertainty of new energy output. Therefore, this paper proposes a multi-agent game operation method of regional integrated energy system based on carbon emission flow. First, this paper establishes a carbon emission flow calculation model for each subject, and proposes a comprehensive tariff model based on the carbon emission flow, which discounts the carbon emissions from the power supply side to the power consumption side. Secondly, considering the interests of each subject, this paper establishes the decision-making model of each subject. And the new energy uncertainty, the cost of energy preference of prosumers, and the thermal inertia of buildings are considered in the decision model. Finally, the model is solved using differential evolution algorithm and solver. The case study verifies that the comprehensive electricity pricing model based on carbon emission flow developed in this paper can play a role in balancing economy and low carbon.

Irrigation Water Use Payments and Policies in Developing Countries

Nowadays, water tariffs in economic developing countries are considered one of the important factors and it is not a secret that one of the reasons for the water crisis in Central Asian Countries is the growing demand for water resources. The resource is becoming scarce like in other continent of earth. It is measured as the most important natural resource and abundant liquid on earth. In this study irrigation water charging case of Uzbekistan and foreign practices, model of tariffs for water services and pricing elements have been analyzed. Irrigation water charging methods in different countries are used in different ways.

Bi-level planning approach for incorporating the demand-side flexibility of cloud data centers under electricity-carbon markets

With the prevalence of cloud computing applications, cloud data centers (CDCs) are proliferating around the world. However, in the context of hybrid energy‑carbon markets environment, the high energy costs and environmental expenses caused by CDC operation are pressing CDC owners to restructure the future development of CDC in a more economical and low-carbon manner. The potential spatio-temporal transferability and reducibility of workloads provides CDCs with significant flexibility in their operations and thus may interact with the power grid as active demand users. Nonetheless, other than private data centers, public CDCs have no direct control over the workloads submitted by terminal cloud users. As such, this paper presents a bi-level model for CDC allocation planning, so as to incorporate cloud service-demand response (CS-DR) from the perspective of a hybrid electricity-carbon market. The upper level pertains to multi-domain resource collaborative planning model, which determines the optimum siting and sizing of CDCs as well as the incentive design for CS-DR program, with the objective of maximizing the total expected benefits of CDC. The lower level models correspond to the market clearing (electricity-carbon tariff model) of Independent system operator (ISO) and the decision-making of cloud users regarding CS-DR participation. The proposed model belongs to a bi-level mixed integer nonlinear programming problem with two non-convex lower levels, which can be intractable in mathematics. To solve such difficult problem, a hybrid solution method combining multiple linearization techniques and reformulation and decomposition (R&D) strategy based on column-and-constraint generation (C&CG) algorithm is developed. The proposed model is demonstrated on a modified IEEE 30-bus test case, and the simulation results verified the effectiveness of the proposed approach.

Implementation of Billing System at Electrical Vehicle Charging Stations in Elektroprivreda BiH

Abstract Electromobility is strongly encouraged in the European Union. Elektroprivreda of Bosnia and Herzegovina (EP BiH) is the only company in BiH that uses Charge Point Management Software. To ensure a functional process of calculation and billing of charging consumption, it is necessary to implement appropriate software solutions. This paper provides a comparative analysis of possible models of ad-hoc charging at electric vehicle charging stations. As a result of a comparative analysis of the advantages and disadvantages of each of the observed variants, a more detailed description of one selected model was given, which, due to its characteristics, as well as readiness for quick implementation in existing environment of EP BiH, proved to be the most adequate solution for business requirements of the company. The paper describes the economic effects of the introduction of the selected billing model, as well as the tariff model for charging.

An orthogeriatric service can reduce prolonged hospital length of stay in hospital for older adults admitted with hip fractures: a monocentric study

BackgroundThe Blue Book (2005), recommended guidelines for patients care with fragility fractures. Together with introduction of a National Hip Fracture Database Audit and Best Practice Tariff model to financially incentivise hospitals by payment of a supplement for patients whose care satisfied six clinical standards), have improved hip fracture after-care. However, there is a lack of data-driven evidence to support its effectiveness. We aimed to verify the impact of an orthogeriatric service on hospital length of stay (LOS)—duration from admission to discharge.MethodsWe conducted a repeated cross-sectional study over a 10 year period of older individuals aged ≥ 60 years admitted with hip fractures to a hospital.ResultsAltogether 2798 patients, 741 men and 2057 women (respective mean ages; 80.5 ± 10.6 and 83.2 ± 8.9 years) were admitted from their own homes with a hip fracture and survived to discharge. Compared to 2009–2014, LOS during 2015–2019, when the orthogeriatric service was fully implemented, was shorter for all discharge destinations: 10.4 vs 17.5 days (P < 0.001). Each discharge destination showed reductions: back to own homes, 9.7 vs 17.7 days (P < 0.001); to rehabilitation units: 10.8 vs 13.1 days (P < 0.001); to residential care: 15.4 vs 26.2 days (P = 0.001); or nursing care, 24.4 vs 53.1 days (P < 0.001). During 2009–2014, the risk of staying > 3 weeks in hospital was greater by six-fold and pressure ulcers by three-fold. The number of bed days for every thousand patients per year was also shortened during 2015–2019 by: 1665 days for discharge back to own homes; 469 days with transfer to rehabilitation units; 1258 days for discharge to residential care, and 5465 days to nursing care. Estimated annual savings (2017 costs) per thousand patients after complete establishment of the service was about £2.7 m.ConclusionsImplementation of an orthogeriatric service generated significant reductions in hospital LOS for all patients, with associated cost-savings, especially for those discharged to nursing care.

Public Innovation Policy Evaluation: Brazilian Electricity Tariff Paid by Consumers

The objective of this study was to evaluate the impact of the SEB public policy of innovation on the average supply tariff (AST) from its implementation in the year 2000 until 2020, considering the tariff moderation foreseen in the RD&amp;I of the SEB, which is aligned with SDG 7 of Agenda 2030. The methodological procedures included (a) a sample consisting of 40% of the market (seven of the one hundred and eleven electricity distributors) of the market (in consumers and billing); (b) a before and after real tariff model (1994–2020) applied through ordinary least squares (OLS) estimation; (c) calculation of the real AST of the sample using the present value (PV) method, updated based on the IPCA as an indexer; (d) calculation of the result of Model 4 before and after and the AST in PV to verify the impact of the SEB’s RD&amp;I public policy on the AST. The results showed that the creation of the innovation contribution (ContribInova) impacted the AST value by 60.95% in terms of real increase. Three electricity purchasing power (EPP) indicators and the electricity purchasing power index (EPPi) were developed and calculated to track the evolution of the AST to help guide the tariff moderation of the SEB and the Brazilian commitment to Agenda 2030 to ensure access to energy services at affordable prices by 2030.

Techno-Economic Potential of V2B in a Neighborhood, Considering Tariff Models and Battery Cycle Limits

To limit climate change, decarbonization of the transportation sector is necessary. The change from conventional combustion vehicles to vehicles with electric drives is already taking place. In the long term, it can be assumed that a large proportion of passenger cars will be battery–electric. On the one hand, this conversion will result in higher energy and power requirements for the electricity network; on the other hand, it also offers the potential for vehicles to provide energy for various systems in the future. Battery–electric vehicles can be used to shift grid purchases, optimize the operation of other components and increase the self-consumption rate of photovoltaic systems. An LP model for the optimal energy management of the neighborhood consisting of buildings with electricity and heat demand, a PV system, a BEV fleet, a heat pump and thermal storage was formulated. The potential of the BEV fleet to provide energy via V2B in the neighborhood was investigated, considering electricity tariff models and individual charging/discharging efficiencies of vehicles and stochastic mobility profiles. The vehicle fleet provides between 4.8kWh−1sqm−1a (flat-fee) and 25.3kWh−1sqm−1a (dynamic tariff) per year, corresponding to 6.7, 9.5% and 35.7% of the annual energy demand of the neighborhood. All tariff models lead to optimization of self-consumption in summer. Dynamic pricing also leads to arbitrage during winter, and a power price tariff avoids peaks in grid draw. Due to individual charging efficiencies, the power supplied by the fleet is distributed unevenly among the vehicles, and setting limits for additional equivalent full cycles distributes the energy more evenly across the fleet. The limits affect the V2B potential, especially below the limits of 20 yearly cycles for flat and power tariffs and below 80 cycles for a dynamic tariff.

Modelling base electricity tariff under the Malaysia incentive-based regulation framework using system dynamics

&lt;p&gt;&lt;span lang="EN-US"&gt;In the context of a single buyer (SB) electricity market, this study provides an electricity tariff model developed using system dynamics (SD). Using data from the Malaysian electricity supply industry (MESI), the model was developed with the intent of evaluating the influence of load variation on Malaysia’s base electricity tariff. Given that Malaysia’s electricity demand has increased significantly over the past few years in unison with the country’s economic growth and modernization, this model is developed to investigate the relationship between the two. Moreover, the lack of a comprehensive MESI upstream market model that can monitor this issue was the impetus for this research. This study employed an SD approach, as it is a well-known technique for simulating complex systems and analyzing the existing dynamism between each variable and each system. This model can be a valuable tool for developing an electrical tariff model. Findings revealed that the base electricity pricing on the MESI upstream market is affected by load growth variation during the 30-year time. Since new power sources are needed to meet demand, the tariff becomes more expensive as the load increases. This model may benefit the utility or generating company plan for future generation.&lt;/span&gt;&lt;/p&gt;

On Net Energy Metering X: Optimal Prosumer Decisions, Social Welfare, and Cross-Subsidies

We introduce NEM X, an inclusive retail tariff model that captures features of existing net energy metering (NEM) policies. It is shown that the optimal prosumer decision under NEM X obeys by a two-threshold policy. The threshold policy yields three household consumption modes: (a) the net-consuming mode where the prosumer consumes more than its behind-the-meter distributed energy resource (DER) production when the DER production is below a predetermined lower threshold, (b) the net-producing mode where the prosumer consumes less than its DER production when the DER production is above a predetermined upper threshold, and (c) the net-zero energy mode where the prosumer’s consumption matches its DER generation when its DER production is between the lower and upper thresholds. Both the thresholds are obtained in closed-form and computed apriori. Next, we analyze the regulator’s rate-setting process that determines NEM X parameters such as retail/sell rates, fixed charges, and price differentials in time-of-use tariffs’ on and off-peak periods. A stochastic Ramsey pricing program that maximizes social welfare subject to the revenue break-even constraint for the regulated utility is formulated. Performance of several NEM X policies is evaluated using real and synthetic data to illuminate impacts of NEM policy designs on social welfare, cross-subsidies of prosumers by consumers, and payback time of DER investments that affect long-run DER adoptions.

An investigation on fairness perception for grid tariff models: Evidence from Denmark

The grid tariff design has become an important issue for green transition and has been understudied. Depending on how costs are allocated to end-users, different network pricing models can have an influence on the success of the green transition. Consumer perceptions of the fairness of varying tariff models are of great importance to policymakers. The objective of this study is to investigate consumer perceptions of fairness of different tariff models in Denmark. These tariff models include capacity charge, transport charge, dynamic tariff, Ramsey, flat tariff, and socialized tariff. A total of 793 usable respondents were included in the analysis. The result indicates that a majority of consumers perceive cost-reflective pricing models to be fair. In contrast, Ramsey pricing was considered to be unfair by most consumers. Furthermore, the heterogeneity in consumer perceptions was captured: the dynamic tariff preferred (56.7%), the transportation tariff preferred (12.1%), and the flat rate preferred (21.2%). The results of this study are expected to contribute to the design of new grid tariff models in Denmark and internationally.