Electricity Tariff Structure Research Articles

Decarbonization through Active Participation of the Demand Side in Relatively Isolated Power Systems

In the context of power system decarbonization, the demand-side strategy for increasing the share of renewable energy is studied for two constrained energy systems. This strategy, which is currently widely suggested in policies on the energy transition, would impact consumer behavior. Despite the importance of studying the latter, the focus here is on decisions regarding the type, location, and timeframe of implementing the related measures. As such, solutions must be assessed in terms of cost and feasibility, technological learning, and by considering geographical and environmental constraints. Based on techno-economic optimization, in this paper we analyze the evolution of the power system and elaborate plausible long-term trajectories in the energy systems of two European islands. The case studies, Procida in Italy and Hinnøya in Norway, are both electrically connected to the mainland by submarine cables and present issues in their power systems, which are here understood as relatively isolated power systems. Renewable energy integration is encouraged by legislative measures in Italy. Although not modeled here, they serve as a backbone for the assumptions of increasing these investments. For Procida, rooftop photovoltaics (PV) coupled with energy storage are integrated in the residential, public, and tertiary sectors. A price-based strategy is also applied reflecting the Italian electricity tariff structure. At a certain price difference between peak and off-peak, the electricity supply mix changes, favoring storage technologies and hence decreasing imports by up to 10% during peak times in the year 2050. In Norway, renewable energy resources are abundant. The analysis for Hinnøya showcases possible cross-sectoral flexibilities through electrification, leading to decarbonization. By fine-tuning electric vehicle charging tactics and leveraging Norway’s electricity pricing model, excess electricity demand peaks can be averted. The conclusions of this double-prospective study provide a comparative analysis that presents the lessons learnt and makes replicability recommendations for other territories.

Community-based transactive energy market concept for 5th generation district heating and cooling through distributed optimization

Fifth-generation district heating and cooling (5GDHC) is an emerging concept that exploits heat sharing among prosumers through a low-temperature bidirectional loop. Coordinating the energy interactions in such a system is a complex problem, typically solved through centralized optimization. In addition to privacy issues for prosumers, centralized optimization can prove too hard to solve for large 5GDHC systems and cannot establish a profit distribution between prosumers. To overcome these drawbacks, this paper develops a community-based transactive energy market framework based on distributed optimization of 5GDHC. The optimization is based on the Jacobi-proximal alternating direction method of multipliers. The approach relies on iterative interactions between the network coordinator and the prosumers, the former adjusting the internal price of thermal energy and the latter adapting their heating and cooling demand. A series of test-case 5GDHC networks involving houses, commercial buildings, data centers and central boilers and chillers were numerically simulated to demonstrate how the proposed framework performs, under three electricity tariff structures (constant, time-of-use or pay for peak). Results show that, for the cases tested, the gap between the proposed approach and global optimization is below 5% and that electricity savings compared to a situation without 5GDHC could reach 40%. The proposed method allowed to dynamically adjust the internal price of thermal energy and the prosumers' demand while considering their thermal dissatisfaction. By facilitating 5GDHC operation, this work could help their practical implementation in the future.

Holistic analysis of consumer energy decarbonisation options and tariff effects

The consumers' perspective on low-carbon technologies is critical to decarbonise their emissions, the effect from the array of modern tariff structures and the dramatic variation in tariff rates on the technology viability is yet to be realised. Here we present a comprehensive holistic approach that includes electrification and hydrogen options to understand the trade-offs in technologies and tariffs for consumers in their energy decarbonisation which is missing from the technology specific analysis in the literature. The novel framework considers all consumer demands simultaneously through combinations of different low-carbon technologies over a 20-year lifetime, linked with conventional and emerging electricity tariff structures. Using the UK as a case study, we found that electrification is more cost-effective than hydrogen for most consumers to reduce their energy emissions and that the lowest 20-year low-carbon solution of air source heat pump, electric vehicle, and photovoltaics may have slightly (9%) higher lifetime cost to the gas boiler and petrol car baseline but can achieve 54% emission reduction using the grid electricity mix and energy tariffs in 2020. In terms of technologies, electric vehicles and solar photovoltaics are the only evaluated technologies that have the potential to reduce customer's energy costs, 8% and 0.2% respectively, alongside emissions reductions, of 28% and 2% respectively. Energy storage technologies, though significantly benefit the grid by unlocking demand-side flexibility, were not economic beneficial to customers until the tariff increase due to the energy crisis. Designing the average day rate of a tariff is most important for adopting electrified heating, on the other hand energy storage use requires low off-peak rates, where we quantified the minimum required difference in tariff peak to off-peak rates to allow energy storage financial justification. This learning can be used to help incentivise consumers to adopt these technologies, allowing greater system benefits.

Barriers to the adoption of social welfare measures in the electricity tariff structure of developing countries: A case of Pakistan

Energy tariff plays an important role in ensuring affordable energy availability in a country. Various developed countries have incorporated social welfare indicators in their electricity tariff structures to support their lower-income groups. The developing countries, riddled with multifaceted challenges in their energy value chains have not taken care of access to affordable energy for the poor (SDG7). Existing literature on developing countries and Pakistan has not sufficiently highlighted the drivers of social welfare mechanisms in the electricity tariff structure for poor households. This study aims at examining the factors contributing to the decline in social welfare for electricity household consumers in Pakistan. The study has utilized a mixed analytical approach, incorporating NVIVO analysis and Q methodology. The results highlighted a lack of regulatory performance, political influence, suboptimal governance, and financial constraints as barriers to enhancing the residential consumer's social welfare in Pakistan. Our findings may help to devise and revise the policies such as power sector subsidies for the determination of better electricity tariffs for the poorer segment of society in Pakistan. Other developing countries may also benefit by improving the relevant policy circumstances (main barriers from this study) of the electricity subsidies for poor households.

The pathway for electricity prosumption in Ghana

The shortfall of the feed-in-tariff (FiT) mechanism led to net metering and net billing, seen as the comprehensive instrument for developing electricity prosumption globally. Following the global trend, Ghana has adopted net metering for its electricity sustainability development. Despite adopting the net metering scheme in Ghana, prosumption faces many challenges. The paper explores the key factors influencing prosumer deployment in Ghana from policy, regulatory and people's perspectives and suggests a better pathway for Ghana's prosuming path. This study reveals several challenges that prosumers face that discourage many people from investing in photovoltaic installations in Ghana. Among the challenges are policy and regulatory gaps, inelastic electricity tariff structure and the unwillingness of distribution system operators to accept prosumers into the grid with the perception of losing the prosumers as consumers.

Solar desalination: A review of recent developments in environmental, regulatory and economic issues

The aim of the current study was to provide a review of recent developments in solar desalination from the viewpoint of environmental, regulatory, and economic aspects. The analysis attempted to give better insight into the larger question of why more solar desalination plants are not being established by reviewing different technologies, drivers, barriers, and markets. Critical barriers which were dependent on the level of regional development were found to be uncertainty of government subsidies and a lack of regulatory policies. A new tool called a Pareto frontier may be utilized to generate optimal points in complex scenarios with a high number of variables. This all-inclusive method should be employed in any major decision-making process. Furthermore, in exciting innovative research studies, a sustainable Janus wood evaporator was developed that overcame many of the current solar desalination problems. While subsidies were crucial in the growth of renewable energy programs, barriers in deployment of solar desalination systems still exist such as low electricity tariff structures and fragmented energy policies. The overall trend was towards integration of renewable energy with conventional sources and energy storage systems.

The Relationship between Electricity Prices and Household Welfare in South Africa

The study examines the relationship between electricity prices and household welfare in South Africa. The study employs a demand system framework on annual time-series data from 2000 to 2018 and the analysis involves the calculation of price elasticities and measurement of welfare changes. The price elasticities in this study are drawn from the linear expenditure demand model. To analyse welfare change, we consider the impact of electricity pricing policies on cost of living (proxied by the consumer price index and households’ expenditure patterns). The study achieves this: (i) by comparing electricity price movements to changes in the rate of inflation between 2000 and 2018; (ii) by regressing total household energy expenditure against household expenditure on electricity, to examine how electricity costs affect a household’s overall energy bills; and (iii) thirdly, by regressing household food expenditure against households’ electricity expenditure to determine how the latter affects a household’s ability to spend on other basic goods and services. The results of the study show: (i) South African household electricity demand is inelastic to changes in price of electricity; (ii) electricity prices in the country increased at a higher rate than the rate of inflation for most of the time during the study period, suggesting that households incurred increased expenditures to achieve their desired utility or satisfy their energy needs during this period; (iii) household total electricity expenditure is positively related to household total energy expenditure, implying that high household expenditure on electricity exerts upward pressure on the overall household energy budgets; and (iv) household total food expenditure is negatively related to household total energy expenditure. This shows that while policy makers achieved significant success with providing physical access to electricity, affordable access to this basic service is still a concern and affects the overall welfare of households in the country. The study recommends a review of the country’s electricity tariff structure to make affordability a key objective. Moreover, the study calls for coordinated efforts in addressing Eskom challenges which have also played a contributing role to the current energy crisis, characterized by an unreliable electricity supply and constantly increasing electricity prices.

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

Controlling electricity storage to balance electricity costs and greenhouse gas emissions in buildings

The optimal management of flexible loads and generation sources such as battery storage systems in buildings is often concerned with minimizing electricity costs. There is an increasing need to managed flexible resources in a way that minimises both costs and carbon emissions. Minimising emissions of grid consumed electricity requires quantification of the carbon emissions intensity of the electricity grid, so first we develop a real-time emission intensity model of the Australian National Energy Market using a power-flow tracing approach. This model reveals that electricity price signals currently do not drive consumers toward using electricity at times of lower emissions. For example, the mean and peak emissions intensity during low electricity tariff periods are the same or slightly higher than those during high tariff periods, while the 30-min wholesale electricity price in each region has no significant correlation with the emissions intensity of electricity consumed in that region. The emissions model is then used to investigate the extent to which controlling a battery storage system to minimise costs under existing electricity tariff structures also leads to minimisation of greenhouse gas emissions for a case study commercial office building. Results show that reducing emissions does indeed come at the expense of increasing costs. For example, annual operating cost savings reduced from 31% to 20% when the battery control was changed from minimising costs to minimising emissions. This has important implications for buildings seeking to reduce emissions as well as for the design of electricity tariffs.

Do Energy Prices drive Inflation in South Africa? An unrestricted VAR Approach

This study was aimed at investigating the effects of energy prices on inflation in South Africa. This was achieved by means of econometric analysis and annual time series data spanning from 1994 to 2020. The findings revealed that electricity tariffs and petrol prices exhibit a positive effect on inflation in South Africa. On the contrary, interest rates and the exchange rate as control variables were found to have a negative effect on the inflation rate. The impulse response function indicated that inflation responds positively to innovations in petrol prices, electricity tariffs and money supply in the medium and long term but responds negatively to innovations in interest rates and exchange rates. Further to this, the variance decomposition function revealed that variations in inflation are largely explained by its own innovations and partially explained by innovations in petrol prices, money supply and interest rates. Lastly, the granger causality analysis showed no evidence of causality between inflation and explanatory variables during the specified period. Given that energy prices place upward pressure on inflation, the study recommends a review of the current fuel and electricity tariff structure to provide the much-needed relief to households and businesses.

Optimizing Conduit Hydropower Potential by Determining Pareto-Optimal Trade-Off Curve

In numerous locations of bulk water supply/distribution systems, energy is dissipated by pressure-reducing devices, whereas it could be recovered by means of turbines or pumps as turbines. These pipe systems, owned and operated by municipalities, water utilities, large water-consuming industries, and mines, could be used as a source of renewable sustainable energy. However, the exploitation of these systems presents several issues related to the complexity of the operational optimization of the hydropower generation facilities and to the potential negative impact on the reliability of the system itself. We have developed a novel procedure to optimize the energy generation in such a conduit system by assessing the interrelationship of storage volumes, demand patterns, operating cycles, and electricity tariff structures. The procedure is a multi-objective genetic algorithm designed to provide a solution to maximize electricity generation and thus revenue and to minimize the risk involved in supplying the demand. A Pareto-optimal trade-off curve is set up, indicating the potential benefit (revenue) versus the reliability index (supply security). The results indicate that a Pareto-optimal trade-off curve was generated from which a solution could be selected which would improve the weekly revenue by up to 7.5%, while still providing a reliable water supply system.

Renewable Energy Development in the Gulf Cooperation Council Countries: Status, Barriers, and Policy Options

The countries of the Gulf Cooperation Council (GCC)—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—hold almost 30% of the world’s total proven oil reserves and around 20% of its total proven natural gas reserves. They are also endowed with a high abundance of renewable energy resources such as solar and wind. Yet, the GCC’s primary energy consumption is still dominated by fossil fuels, and the share of renewable energy still does not exceed 1%. Drawing on secondary data, including journal articles, governmental and companies’ websites, and reports and newspaper articles, this paper assesses the reasons behind their underutilization of renewable energy resources. Whereas technical and economic feasibility issues had been identified as the main barriers to slow the uptake of renewable energy technologies in the GCC, this paper uncovered that various additional factors have remarkably influenced such delays. High hydrocarbon subsidies, low electricity tariff structure, fragmented energy policy, the absence of dedicated renewable energy regulator and regulatory framework, and a highly controlled power market are major barriers to renewable energy adoption in the GCC. The paper concludes with policy options to inform scaling up the adoption of renewable energy in the GCC.

IMPROVE THE INCREMENTAL BLOCK TARIFFS OF ELECTRICITY: TO HARMONIZE PRICING POLICY TARGETS IN THE NEW CONTEXT OF POWER SUPPLY AND DEMAND IN VIETNAM

The existing retail electricity tariff for households in Vietnam is the incremental block structure. However, the most recent revision of the electricity tariff structure was in 2014 which it was 7 years - a long period of change in conditions of electricity supply and consumption leading to the need to adjust this structural price appropriately. This article provides an in-depth analysis of the current residential block tariff of residential electricity use to identify shortcomings, thereby, for building options to improve this incremental block tariff structure to ensure the harmonization of different pricing targets especially the equity, efficiency and promote the electricity saving, in the new context of electricity supply and demand in Vietnam.Keywords: Electricity pricing policy, incremental block tariff, Electricity of VietnamJEL Classifications : D4, Q31, Q41, Q43. Q48DOI: https://doi.org/10.32479/ijeep.11534

Sources of inequality in household electricity consumption: evidence from Taiwan

ABSTRACT This study examined the inequality of household electricity consumption in Taiwan over 1981–2017. The concentration index results indicated that richer households consume more electricity use per capita than poorer households, while the Kakwani index results revealed that the regressivity of electricity expenditure with respect to income distribution gradually intensified. Household size, household income, and air conditioner ownership are the most important sources of the inequality in electricity use. The inequality in electricity use concentrated among the high-income households decreased due to the declining income elasticity, the pro-rich distribution of household size, and increasing prevalence of household appliances. The distribution of household size across the income groups had changed. These results imply that the electricity tariff structures should take household size into consideration. It is important to develop identification approaches, integrating information about the characteristics of households and their occupants, so as to support utilities identify and classify the clients.

Demand response through reject water scheduling in water resource recovery facilities: A demonstration with BSM2

The objective of this paper is to determine the importance of integrating peak demand mitigation and future energy pricing structures for process modelling of conventional water resource recovery facilities (WRRFs) when evaluating energy cost and control strategies. The well-established benchmark simulation model (BSM2) is used to monitor energy usage, and a detailed holistic study of different flow streams is performed in order to establish potential opportunities for flexible control of WRRF energy demand. Secondly, a detailed framework is introduced to optimize scheduling control strategies for the reject water stream while considering peak electricity demand avoidance as well as completing a comprehensive energy cost model based on current and anticipated future energy tariff structures. The reject water scheduling strategies, without other active controls (e.g. aeration), revealed 63.4% average peak demand mitigation and €10,755 cumulative annual energy cost savings on a 100k population equivalent WRRF without a deterioration in effluent quality. Analysis of different reject water scheduling control strategies shows that reject water scheduling can be an effective tool for energy cost optimisation under alternative electricity tariff structures. These strategies also deliver electricity peak demand mitigation.

Aggregation of Households in Community Energy Systems: An Analysis from Actors’ and Market Perspectives

In decentralized energy systems, electricity generated and flexibility offered by households can be organized in the form of community energy systems. Business models, which enable this aggregation at the community level, will impact on the involved actors and the electricity market. For the case of Germany, in this paper different aggregation scenarios are analyzed from the perspective of actors and the market. The main components in these scenarios are the Community Energy Storage (CES) technology, the electricity tariff structure, and the aggregation goal. For this evaluation, a bottom-up community energy system model is presented, in which the households and retailer are the key actors. In our model, we distinguish between the households with inflexible electricity load and the flexible households that own a heat pump or Photovoltaic (PV) storage systems. By using a game-theoretic approach and modeling the interaction between the retailer and households as a Stackelberg game, a community real-time pricing structure is derived. To find the solution of the modeled Stackelberg game, a genetic algorithm is implemented. To analyze the impact of the aggregation scenarios on the electricity market, a “Market Alignment Indicator” is proposed. The results show that under the considered regulatory framework, the deployment of a CES can increase the retailer’s operational profits while improving the alignment of the community energy system with the signals from the electricity market. Depending on the aggregation goal of the retailer, the implementation of community real-time pricing could lead to a similar impact. Moreover, such a tariff structure can lead to financial benefits for flexible households.

Peak Shaving through Battery Storage for Low-Voltage Enterprises with Peak Demand Pricing

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00–31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency).

Multiagent-Based Transactive Energy Management Systems for Residential Buildings With Distributed Energy Resources

Proper management of building loads and distributed energy resources (DER) can offer grid assistance services in transactive energy (TE) frameworks besides providing cost savings for the consumer. However, most TE models require building loads and DER units to be managed by external entities (e.g., aggregators), and in some cases, consumers need to provide critical information related to their electricity demand and usage, which hampers their privacy. This article introduces a transactive energy management framework for the buildings in a residential neighborhood to address grid overloading and cost optimization of the buildings. The decentralized coordination for the energy management system is realized by using a multiagent system architecture, which provides the consumers with full decision-making authority and preserves their privacy. A new event-triggered transactive market algorithm is developed, where the buildings trade energy to maximize profits, while the regional grid operator procures energy-supply flexibility of active consumers to prevent transformer overloading. A two-stage energy management system is developed for the residential buildings that schedules building loads and DER units in day-ahead stage to minimize cost and inconveniences for the consumer while participating in the real-time transactive market to maximize profits. An optimal bidding model is developed for the buildings that incorporates the degradation of residential storage devices for energy trading. Case studies and analyses with actual Australian building data and electricity tariff structures indicate the efficacy of the proposed methodology for effective mitigation of transformer overloading at a negligible cost compared to transformer replacement cost. Results also indicate that the proposed system can provide 15–20% cost savings for the consumers while minimizing their inconveniences and degradation of storage devices.

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system.

Impact of advanced electricity tariff structures on the optimal design, operation and profitability of a grid-connected PV system with energy storage

The increasing penetration of residential photovoltaics (PV) comes with numerous challenges for distribution system operators. Technical difficulties arise when an excess of PV energy is injected into the grid, causing voltage rise or overloading of the lines. Economic challenges appear because PV owners and consumers are not participating equally in the grid costs. Indeed, PV owners benefit by self-consuming their PV production and by gaining additional revenues when they sell their PV surplus to the grid. Hence, they lower their grid costs. In this paper, we propose a mixed-integer-linear programming approach to solve the design and operation of a PV and battery system efficiently. We use this tool to benchmark five different tariff scenarios, which include real-time pricing, a capacity-based tariff, and a block rate tariff, and evaluate their effect on the design and operation of the system. Carefully tailored metrics show the impact of these tariff structures on the trade-off between the economic viability of privately owned energy systems and their grid usage intensity. Considering both aspects, we show that a block rate tariff is the most promising approach and that capacity-based tariffs rely on PV curtailment alone to curtail the generation peaks.