Academic literature on the topic 'Time-Of-Use tariffs of electricity'

This master thesis evaluates the incentives of a newly implemented market controlled network tariff by analyzing consumption data and constructing a time-differentiated debiting model. The tariff was implemented by Sandviken Energi Elnät AB and the thesis evaluates its customers consumption data compared to data provided by Sundsvall Elnät AB. The differences in data is evaluated by statistical tests of Students t-test, Bayesian t-test and χ2-test with the result that no statistically significant change in user pattern can be found and thus an elucidation of the incentives must be made in the form of a hourly time-differentiated debating model. The thesis also evaluates the cost incentives of the model compared to spot prices where it is shown that the tariff model can benefit much from the spot prices hourly incentives in its hourly time-differentiated model. Five time-differentiated models were constructed and presented where three uses a color coding scheme. The conclusion is that a color coded time-differentiated tariff should give the costumers clear and cost-effective incentives.

The Swedish electricity system is transitioning due to the establishment of climate policy goals and trends related to technology and demographics. The transition has resulted in an increased demand for electricity. The increased demand for electricity in combination with lack of forecasts, planning and coordination between actors in the electricity sector has led to the occurrence of grid congestion. Extending the network is time-consuming and requires substantial investments. Instead, an alternative is to utilise the available grid capacity more efficiently by implementing flexibility solutions. Flexibility can be achieved by implementing incentives such as grid tariffs. This solution has recently gained much attention in Sweden, but it is not apparent how grid tariffs should be designed. The purpose of this thesis is to investigate how distribution grid tariffs could be designed to incentivise different actors to contribute to flexibility in a way that results in an efficient use of the electrical grid. A qualitative study was performed, collecting empirical data through semistructured interviews with actors in the Swedish electricity market. The aim is that the results from this thesis will act as a basis for DSOs planning to design grid tariffs with the purpose to utilise the grid more efficiently. The findings present a ToU capacity charge with off-peak periods that are free of charge as the preferable main price signal in the tariff to achieve efficient utilisation of the grid. It is further argued that other structural elements can complement the ToU capacity charge. A small fixed charge could be added in order to contribute to the cost reflectiveness of the grid tariff. A small energy charge could be incorporated in order to provide consumer with incentives to be flexible below the current metered maximum power and strengthen the signal from the ToU capacity charge. A small energy charge can avert difficulties related to providing incentives below the current metered maximum, as it still can provide some incentives to be flexible, or strengthen the signal from the ToU capacity charge. Further, the energy charge can ensure sustainability if customers respond well to a ToU capacity charge and to compensate solar PV customers. Furthermore, recommendations to further enable the grid tariffs potential to provide price signals include shifting the focus of the revenue cap from CapEx to OpEx and exploring the hampering signals of the energy tax as well as contradicting price signals from the wholesale electricity price.<br>Det svenska elsystemet genomgår en förändring till följd av införandet av klimatmål och trender relaterade till teknik och demografi. Denna förändring har resulterat i ett ökat effektbehov. Ett ökat effektbehov i kombination med bristande prognostisering, planering och samordning mellan aktörer inom elsektorn har lett till uppkomsten av kapacitetsbrist. Att bygga ut elnätet är tar tid och kräver större investeringar. Ett alternativ är att istället utnyttja det befintliga elnätet mer effektivt genom att implementera flexibilitetslösningar. Flexibilitet kan uppnås genom att införa incitament i form av elnätstariffer. Denna lösning har nyligen fått mycket uppmärksamhet i Sverige, men det är inte klart inte hur dessa elnätstariffer ska utformas. Syftet med detta arbete är att undersöka hur distributionsnätets tariffer kan utformas för att stimulera olika aktörer att bidra med flexibilitet på ett sätt som resulterar i en effektiv användning av det befintliga elnätet. En kvalitativ studie genomfördes där empiriska data samlades in genom semistrukturerade intervjuer med aktörer på den svenska elmarknaden. Syftet är att resultaten från detta arbete ska fungera som ett underlag för nätägare som planerar att utforma elnätstariffer med syftet att utnyttja nätet mer effektivt. Resultaten visar att en ToU-effektavgift med gratis off-peak perioder bör vara den huvudsakliga prissignalen i en elnätstariff som ämnar att utnyttja det befintliga nätet mer effektivt. Det visar även att andra strukturella element kan komplettera ToU-effektavgiften. En mindre fast avgift kan adderas i syfte att göra elnätstariffen mer kostnadsriktig. En mindre energiavgift kan införas för att ge kunder incitament att vara flexibla även under den nuvarande uppmätta maximala effekten och stärka signalen från ToU-effektavgiften. Vidare kan energiavgiften säkerställa tillräckliga intäkter för nätägaren om kunderna svarar bra på en ToU-effektavgift och för att kompensera kunder med solceller. Ytterligare rekommendationer för att möjliggöra prissignaler genom elnätstariffer inkluderar att skifta fokus på intäktsramen från CapEx till OpEx och utforska de hämmande prissignalerna från energiskatten och de motstridiga prissignalerna från elhandelspriset.

Les problèmes de planification liés aux tarifs multi-agents et au temps d'utilisation de l'électricité sont devenus des sujets de recherche d'actualité pour améliorer la satisfaction des clients et équilibrer l'offre et la demande en électricité. Les existant travaux révèlent que : 1) la plupart des problèmes d'ordonnancement se concentrent sur des configurations bi-agents ; 2) la plupart des recherches sur l'ordonnancement dans le cadre des tarifs horaires limitent aux machines uniques ou parallèles ou aux ateliers simplifiés ; et 3) très peu d'études prennent en compte des hypothèses réalistes, telles que les arrivées des tâches et les dates d'échéance souhaitées par les clients. Pour combler ces lacunes, cette thèse explore trois nouveaux problèmes d'ordonnancement flowshop qui intégrant successivement l'aspect de multi-agents et de tarifs horaires de l'électricité, tout en prenant en compte des hypothèses réalistes telles que les dates disponibles de tâches, les dates d'échéance et les activités de maintenance. Premièrement, un problème d'ordonnancement de flowshop et multi-agents avec dates de disponibilité et sous deux scénarios est étudié. L'objectif est de minimiser le temps total de réalisation des agents et le retard maximum. Pour obtenir une solution optimale pour les instances de petite taille, un algorithme de séparation et évaluation combinant des bornes inférieures et des stratégies d'élagage est développé. Pour les instances de taille moyenne, un algorithme co-évolutif intégrant des techniques d'apprentissage par renforcement est proposé pour obtenir des solutions proches d'optimum. Des expériences numériques démontrent l'efficacité des méthodes proposées.Deuxièmement, un bi-objectif problème d'ordonnancement de flowshop avec tarifs horaires de l'électricité est adressé. L'objectif est de trouver le meilleur compromis entre le coût total de l'électricité et le retard maximum. Basé sur l'analyse du problème, des inégalités valides sont conçues pour réduire l'espace de recherche.Ensuite, une méthode de contrainte ε combinant taille de pas maximale et stratégie d'inversion est proposée pour obtenir le front de Pareto. Pour les instances de taille moyenne et grande, un algorithme d'optimisation des mouches à fruits en deux étapes est appliqué pour obtenir un front de approché. Les performances des algorithmes proposés sont évaluées à travers diverses expériences numériques.Enfin, un problème d'ordonnancement de flowshop et multi-agents avec tarifs horaires de l'électricité est étudié. L'objectif est de minimiser le temps total de réalisation des agents et le coût total de l'électricité, simultanément. Un nouveau algorithme de séparation et évaluation est conçu pour résoudre le problème, dans lequel une stratégie de branchement à deux nœuds et des règles d'élagage sont fournies pour réduire efficacement le temps de calcul. La performance de l'algorithme proposé est évaluée en comparant les résultats proposés par un solveur commercial CPLEX<br>Multi-agent and time-of-use (ToU) tariff of electricity related scheduling problems have become hot research topics in production scheduling to improve customer satisfaction and balance electricity supply and demand.Existing works reveal that: 1) most multi-agent scheduling focuses on bi-agent problems; 2) most scheduling research under ToU tariffs addresses single and parallel machine, or simplified shop environments; and 3) very few studies consider real-world assumptions, such as dynamic job arrivals and customer-desired due dates.To bridge these research gaps, this thesis investigates three new flow shop scheduling problems which successively integrates the aspect of multi-agent and ToU tariffs, considering practical assumptions such as release dates, due dates and maintenance activities. Firstly, a multi-agent FSS problem with release dates under two scanerios is addressed. The objective is to minimize the total completion time of the agents and the maximum lateness. To obtain an optimal solution for small-size instances, a branch-and-bound (B&amp;B) algorithm combining lower bounds and pruning strategies is developed. For medium-size instances, a co-evolutionary algorithm incorporating reinforcement learning techniques is proposed to obtain near-optimal solutions. Numerical experiments demonstrate the effectiveness of the proposed methods.Secondly, a bi-objective FSS problem under ToU tariffs is investigated. The objective is to find the best trad-off between the total electricity cost and the maximum lateness. Based on problem analysis, valid inequalities are designed to to reduce the search space. And then, an ε-constraint method combining maximum step size and inversion strategy is proposed to obtain the Pareto front. For medium- and large-size instances, a two-stage fruit fly optimization algorithm is applied to obtain an approximate Pareto front. The performance of the proposed algorithms is evaluated through various numerical experiments.Finally, a bi-objective multi-agent FSS problem under ToU tariffs is studied. The objective is to simultaneously minimize the total completion time of agents and the total electricity cost. A new B&amp;B algorithm is designed for the problem, in which a two-node branching strategy and pruning rules are provided to effectively reduce the computational time. The performance of the proposed algorithm is evaluated by comparing the results proposed by a commercial solver CPLEX

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.<br>Libyan government