236 research outputs found
The impact of an energy crisis on the residential consumers’ consumption behavior based on a Finnish case study
No full textConsumer enrollment in residential demand response: Implications across diverse societies
No full textThe transition of a conventional energy system to a sustainable one requires the availability of flexible loads on the consumption side. Coupling several individual residential consumers can provide a high degree of flexibility, which can help the energy system during times of need. This paper aims to analyze the potential enrollment of residential consumers in demand response across different societies by using an agent-based model. The motivators determining consumer enrollment are personal satisfaction, the neighborhood effect, and the social effect. In this paper, three different societies, in which all consumers have one major motivator fixed, are considered. A Monte Carlo analysis was performed to address the randomness associated with assigning different neighborhoods, friends, and expected annual savings of consumers. The highest enrollment rate was observed in April, and the lowest between June and September for the societies where consumers had personal satisfaction and the social effect as their major motivators. The society in which consumers were mainly motivated by the neighborhood effect was highly dependent on the random assignment of the neighborhood, and the enrollment rate was independent of the electricity prices, which, in turn, resulted in complete enrollment or disenrollment of the neighborhood in the society
What happens after electrification? Exploring the evolution of appliance adoption in rural Kenya
No full textResidential consumer enrollment in demand response: An agent based approach
No full textResidential consumers play an important role in the sustainable transition of the energy system by leveraging their household loads for demand response (DR). This paper aims to analyze the enrollment rates of residential consumers within DR through an agent-based model (ABM). Both economic and noneconomic (social/behavioral) parameters that influence the consumer enrollment in DR are considered. An energy management model, a home energy management system (HEMS), is used to identify the potential economic savings of consumers enrolling in DR. Consumers are randomly assigned to different neighborhoods and have different social relationships (e.g., friends, neighbors), which, in turn, influences their decision-making in the ABM. The results of this paper highlight the indirect relationship of expected annual savings and direct relationship of the share of consumers having electric vehicles (EV), photovoltaics (PV), and battery energy storage systems (BESSs) on the DR enrollment rates. Based on the enrollment rates, the maximum energy savings were obtained in April and the minimum during the last quarter of the year. Monte Carlo analysis is employed to handle the randomness associated with different variable selections, which provides a +/- 10% variation of consumer enrollment rate in DR. The results of this study have practical implications for energy flexibility in the residential sector
Addressing myths of residential consumers regarding demand response*
No full textThe rising need for energy flexibility has paved the way to explore different solutions in various sectors. The residential sector represents one group of consumers who have very low individual flexibility, but due to their large numbers when coupled together, can help the energy system during times of need. This study investigates residential consumers' preferences for Demand Response (DR) programs, aiming to debunk prevalent myths and provide insights for stakeholders. Analyzing data across demographic divisions like gender, age, education level, household composition, and type, our findings challenge the existing literature, highlighting the need for tailored strategies to effectively promote residential DR adoption. This study not only offers valuable insights into residential DR motivators but also underscores the importance of adapting strategies to reflect the consumer background and meet evolving consumer needs
Assessing the Economic and Environmental Benefits of Residential Demand Response: A Finnish case study
No full textThe residential sector has been known to have a few flexible loads and the current utilization of demand response within the residential sector is minuscule, with a major limitation being low economic incentives for consumers, and possible lack of information related to potential benefits. This paper focuses on the economical and environmental benefits of Finnish residential demand response and provides an analysis of the effects of different demand response programs and user decisions on the considered economic and environmental indicators. The results from this paper can provide the necessary information for consumers regarding different demand response strategies and their potential trade-offs, so they can make an informed decision in the future regarding demand response.Post-print / Final draf
Forecast or Nowcast to Predict Electricity Prices? The Role of Open Data
No full textThere are two primary methods for predicting electricity prices: forecasting and nowcasting. This study compares these approaches by employing various machine learning algorithms to forecast electricity prices. The nowcast algorithms are trained on data spanning from 2018 to 2021 and evaluated for the years 2022 and 2023, during which the energy system of Finland underwent significant changes, whereas the forecasting algorithms use the data for the previous 90 days to predict the next-day prices. Among nowcasting methods, Random Forest emerged as the top-performing algorithm, while the k Nearest Neighbor algorithm performed best in the forecasting approach. Despite achieving relatively low prediction errors, the predicted prices for 2022 and 2023 diverged notably from the actual prices. This discrepancy underscores the challenge of accurately predicting prices using current open data sources, particularly in scenarios involving significant alterations in the energy system. Consequently, the ability to anticipate price changes based on energy system transformations remains elusive, impacting research efforts focused on price prediction under future-specific circumstances.Post-print / Final draf
Toward residential flexibility—Consumer willingness to enroll household loads in demand response
No full textConsumers of the future play an important role in the energy system by leveraging their household loads to be flexible through demand response (DR) during a high network stress. This study aims to identify the consumers’ Willingness To Enroll (WTE) their different household loads in DR considering consumer preferences for both financial gains and emission reductions. To study this, a questionnaire survey was administered to 1,468 Finnish residential consumers, and several statistical methodologies were used to draw key findings regarding consumer socioeconomic and demographic characteristics on their WTE their household loads in DR. The key results of the study are: First, among the household loads, heating and electric appliances have a higher consumers’ willingness to enroll than EVs. Second, within the incentives, consumers preferred financial incentives to environmental incentives. Third, the expected compensations for consumers were 100 €/annum for appliances and EVs and 200 €/annum for heating. The results of this study have clear practical implications for energy flexibility in the residential sector. Further, the paper discusses the corresponding policy implications that are essential for a widespread DR adoption in the future
Computing system for analysing the effects of the benchmarking of the electricity distribution companies
No full textTässä diplomityössä oli tavoitteena suunnitella ja toteuttaa verkkoliiketoiminnan tehokkuusmittauksen ohjausvaikutusten analysointijärjestelmä.
Verkkoliiketoiminta on monopoliasemassa olevaa liiketoimintaa, jossa ei ole kilpailusta johtuvaa pakotetta pitää liiketoimintaa tehokkaana ja hintoja alhaisina. Tämän vuoksi verkkoliiketoiminnan hinnoittelua ja toiminnan tehokkuutta tulee valvoa viranomaisen toimesta. Tehokkuusmittauksessa käytettäväksi menetelmäksi on valittu DEA-menetelmä (Data Envelopment Analysis).
Tässä työssä on esitelty DEA-menetelmän teoreettiset perusteet sekä verkkoliiketoiminnan tehokkuusmittauksessa havaitut ongelmat. Näiden perusteella on määritelty analysointijärjestelmältä vaadittavat ominaisuudet sekä kehitetty kyseinen järjestelmä.
Tärkeimmiksi järjestelmän ominaisuuksiksi osoittautuivat herkkyysanalyysin tekeminen ja etenkin sitä kautta suoritettava keskeytysten hinnan laskeminen sekä mahdollisuudet painokertoimien rajoittamiselle.
Työn loppuosassa on esitelty järjestelmästä saatavia konkreettisia tuloksia, joiden avulla on pyritty havainnollistamaan järjestelmän käyttömahdollisuuksia.The aim of this work is to develop a computing system for analysing the effects of the benchmarking of the electricity distribution companies.
Electricity distribution business operates as a so-called natural monopoly and there is no pressure from the markets to keep prices and costs at reasonable level. Therefore the operational efficiencies of the distribution companies and pricing of the network services are supervised by an authority. The benchmarking method is DEA (Data Envelopment Analysis).
The theoretical methods of DEA and the problems discovered in the efficiency benchmarking of the distribution companies are presented. The features of the analysing system designed to solve discovered problems are defined based on the theoretical methods of DEA.
Major features of system turned out to be sensitivity analysis, determining the outage costs and weight restrictions. Results from calculations performed are presented to illustrate the usability of analysing system
Performance benchmarking and incentive regulation – considerations of directing signals for electricity distribution companies
No full textAfter the restructuring process of the power supply industry, which for instance in Finland took place in the mid-1990s, free competition was introduced for the production and sale of electricity. Nevertheless, natural monopolies are found to be the most efficient form of production in the transmission and distribution of electricity, and therefore such companies remained franchised monopolies. To prevent the misuse of the monopoly position and to guarantee the rights of the customers, regulation of these monopoly companies is required.
One of the main objectives of the restructuring process has been to increase the cost efficiency of the industry. Simultaneously, demands for the service quality are increasing. Therefore, many regulatory frameworks are being, or have been, reshaped so that companies are provided with stronger incentives for efficiency and quality improvements. Performance benchmarking has in many cases a central role in the practical implementation of such incentive schemes.
Economic regulation with performance benchmarking attached to it provides companies with directing signals that tend to affect their investment and maintenance strategies. Since the asset lifetimes in the electricity distribution are typically many decades, investment decisions have far-reaching technical and economic effects.
This doctoral thesis addresses the directing signals of incentive regulation and performance benchmarking in the field of electricity distribution. The theory of efficiency measurement and the most common regulation models are presented. The chief contributions of this work are (1) a new kind of analysis of the regulatory framework, so that the actual directing signals of the regulation and benchmarking for the electricity distribution companies are evaluated, (2) developing the methodology and a software tool for analysing the directing signals of the regulation and benchmarking in the electricity distribution sector, and (3) analysing the real-life regulatory frameworks by the developed methodology and further develop regulation model from the viewpoint of the directing signals. The results of this study have played a key role in
the development of the Finnish regulatory model.ei tietoa saavutettavuudest
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