Search

By advancement and vogue of smart grid technologies, there is a strong attitude toward utilizing different strategies for participating in demand response (DR) programs in electricity markets. DR programs can be classified into two main categories namely incentive-based programs (IBPs) and time-based rate programs (TBRPs). In this paper, an improved incentive-based DR (IBDR) model is proposed. In our proposed IBP, the concept of elasticity is improved where it depends not only on the electricity price, but also is a function of consumption hour and customer type. In this program, the incentive value which is paid to the participating consumers is not a fix value and relates to the peak intensity of each hour. The proposed IBP can participate in both of day-ahead and intra-day electricity markets. The property of considering intra-day market enables consumers to provide maximum DR if possible. The proposed model is implemented on peak load curve of Spanish electricity market and a 200-unit residential complex. Different scenarios are considered to show effectiveness of the proposed DR model from various aspects including peak shaving as well as economic indices. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to analyze and propose the United Arab Emirates (UAE) plan of Renewable Energy mix in 2030 to achieve the government target of reducing the greenhouse gas emissions of CO 2 while maintaining the electricity price to a minimum. The study includes many proposals of the energy mix for electricity to achieve the target, and a comparison study to IRENA's proposal to select the most suitable energy mix plan in terms of CO 2 reduction while maintaining the electricity price. The analysis has been conducted in two different cases: the first case analyzed where the government of UAE does not implement CO 2 taxation of hydrocarbon fuels used to generate electricity; however, the second case analyzed if the government apply CO 2 taxations what would the results be. Further on, calculations of the surplus energy were implemented for future studies on utilization of the excess energy or reducing the power capacity. This paper provides a background analysis of UAE's electricity consumptions and future government plans. [ABSTRACT FROM AUTHOR]

Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan. [ABSTRACT FROM AUTHOR]

The influence of different control strategies and boundary conditions on heat pump system performance are investigated in this study and the trade-off between complexity and performance of different controllers is addressed. For this purpose five different control approaches for a variable speed air source heat pump in a multi family house are compared for three different use-cases. The used controls differ in complexity and the use of external input data like price and weather forecasts. The use-cases are: Constant electricity prices, time variable electricity prices and PV self-consumption. Four different rule-based controllers are compared to a convex MPC approach, presented in this work. Results show that the MPC approach reduces annual operating cost by 6–11% for constant electricity prices and 6–16% in the case of variable electricity prices. Rule-based approaches lead to cost reductions of 2–4%. MPC could increases PV self-consumption from 56% to 58% up to 64–71%. The rule base approaches are found computationally less demanding and easier to design. However fine-tuning has been considerable work and with changing boundary conditions rules had to be readjusted. It showed that increasing thermal storage without MPC is not beneficial and optimised controls are a prerequisite to benefit from increased storage sizes. [ABSTRACT FROM AUTHOR]

This paper developed an agent-based model (ABM) to explore the energy saving potentials (ESPs) of various types of appliances in offices under different pricing mechanisms. The model included four types of commonly used appliances in office buildings: an air conditioner (AC), computers, lights and a basic load. The total ESPs of the entire office are 6.7% and 17.4% on the second and the third price tier of the tiered pricing mechanism (TEP), while the ESPs are 11.8% and 14.2% under the peak-valley pricing (PVP) and critical peak pricing (CPP), respectively. Within different types of appliances, AC consumes the largest amount of electricity, over 50%, while the ESPs of the AC under different pricing mechanisms are only 6.9–12.1%. In contrast, the lights have the biggest ESP, i.e. 14.1–53.4%, under various pricing levels. Both the pricing mechanisms of PVP and CPP only have the effect of peak clipping and do not have a significant effect of valley filling, since there is no people working in the office during the valley price period. The maximum ESP, which is based on people’s maximum-saving behavior, is much larger than the ESPs on the basis of people’s ordinary consumption patterns. This implies the importance of improving people’s awareness of energy saving and refining their behaviors. Lastly, the model developed in this study provides a generic platform for simulating many types of energy systems and is very effective for handling the complicated relations between different types of technology and the way how they are used and interacted with each other. ABMs have very good adaptability and capacity in simulating energy systems. [ABSTRACT FROM AUTHOR]

Demand response mechanisms and load control in the electricity market represent an important area of research at the international level: the trend towards competition and market liberalization has led to the development of methodologies and tools to support energy providers. Demand side management helps energy suppliers to reduce the peak demand and remodel load profiles. This work is intended to support energy suppliers and policy makers in developing strategies to act on the behavior of energy consumers, with the aim to make a more efficient use of energy. We develop a non-linear optimization model for the dynamics of the electricity market, which can be used to obtain tariff recommendations or for setting the goals of a sensibilization campaign. The model comes in two variants: a stochastic version, designed for residential electricity consumption, and a deterministic version, suitable for large electricity users (e.g., public buildings, industrial users). We have tested ourmodel on data from the Italian energy market and performed an extensive analysis of different scenarios. We also tested the optimization model in a real setting in the context of the FP7 DAREED project (http://www.dareed.eu/), where the model has been employed to provide tariff recommendations or to help the identification of goals for local policies. [ABSTRACT FROM AUTHOR]

An Internal Reforming Solid Oxide Fuel Cell (IRSOFC) is modeled thermodynamically; a Horizontal Axis Wind Turbine (HAWT) is designed; the combined IRSOFC-HAWT system should create a reliable source of electricity for the demand of a village located in Manjil, Iran. The output power of HAWT is unstable, but by controlling the fuel rate for the IRSOFC it is possible to have a stable power output from the combined system. When the electricity demand is over the peak or the wind speed is low/unstable/significantly high, the generated power may not be sufficient. To solve this problem, two scenarios are considered: connecting to the grid or using a Pumped Hydro Storage (PHS). For the second scenario, the extra produced electricity is saved when the production is more than demand and can be used when the extra power is needed. The economic analysis is done based on the economic conditions in Iran. The results will show a period of return about 9.5 and 13 years with the levelized cost of electricity about 0.0747 and 0.0882 $/kWh for the first and second scenarios, respectively. Furthermore, effects of some parameters such as the electricity price and the real interest rate are discussed. [ABSTRACT FROM AUTHOR]

The features of the electricity, as well as the rules of the competitive electricity markets, create the need of accurate predictions of electricity demand and price in order to anticipate decisions. Mainly, the prediction task in energy markets has been studied in the literature with the aim of obtaining scalar (hourly, daily, …) forecasts given scalar (and/or, less frequently, functional) historical data. This paper provides two methods to predict next-day electricity demand and price daily curves given information from past curves. They are based on using robust functional principal component analysis and nonparametric models with functional both response and covariate. In addition, the nonparametric proposal is extended to incorporate, in a linear way, exogenous scalar covariates. Results of these methods for the electricity market of mainland Spain, in year 2012, are reported. Their accuracy is compared with that of a naïve method as well as with the corresponding to combining forecasts. Scalar versions are also included in the comparative study. This work extends and complements the methods and results in Vilar et al. (2012), focused on scalar forecasts. [ABSTRACT FROM AUTHOR]

Due to the relevance of fossil fuels in the electricity matrix in Spain, the electrical sector plays a crucial role in mitigation policies such as carbon taxes. Increased prices of electricity can act as an incentive to enhance energy efficiency contributing to CO2abatement. This paper evaluates a tax on electricity consumption (ECT). Focusing on energy efficiency commitments for Spain as established by EU Authorities for Horizon 2020 (H2020), a pricing model was created to assess economic impacts and its effectiveness in meeting this commitment. The analysis was performed by considering two scenarios, without (Scenario 1) and with (Scenario 2) tax recycling between the new tax and employer-paid social security benefits or contributing to price stability. In Scenario 2, the tax reform is achieved with tax recycling, offsetting the introduction of the ECT by reducing employer-paid social security payments. Two alternative restrictions on the tax reform were considered for the simulation of Scenario 2. In the first case, a restriction was imposed to ensure revenue neutrality (2-I). In the second case, the restriction ought to maintain price stability (2-II). Results from different scenarios offer an important range of possibilities for policy decisions. The results show that with a tax rate equal to 1%, there is a remarkable reduction of CO2emissions from the electricity sector, and the same happens with other sectors that the literature identifies as drivers of such emissions. [ABSTRACT FROM PUBLISHER]

This article presents a new approach to the energy efficiency of households based on smart grid technologies applied to the existing power grid. The idea is to make the electrical appliances capable of actively responding to the condition of the upstream grid,e.g., the electricity price, which, under market environments, is passed to end-use customers through retailers or load aggregators. This both saves on the electricity bill for customers and improves the energy efficiency of the system as a whole. The key element is advanced metering infrastructure, which performs two main functions: (1) computing the so-called control policy for electrical appliances with anticipated data and (2) real-time control based on the above control policy and actual measurements. By stochastic optimization, the proposed scheme is capable of monitoring the uncertainty related to the electricity consumption in households,e.g., temperature and/or time and quantity demanded, etc. In addition, with the physical model taken into account, the problem can be applied to various appliances, including what were considered critical loads. The proposed scheme was tested in heat, ventilation, and air-conditioning systems; the simulation result showed the effectiveness in comparison with the traditional (on/off) scheme based on thermostats. [ABSTRACT FROM PUBLISHER]

The authors estimate price-responsiveness of the residential customers with increasing residential PV penetration and project future electricity sales to the residential sector considering various future PV penetration scenarios. This projection is potentially useful for utilities in their resource planning and ratemaking processes as they formally incorporate the expected reduction in residential electricity demand due to increased penetration of distributed generation. [ABSTRACT FROM AUTHOR]

In this paper we study the spatial and temporal distribution of the wind and hydro resources, together with electricity demand and prices, with the objective to gain insights on the trade-offs of developing wind power in different parts of the country. It is particularly important to understand the impacts of a high penetration level of wind power on an electricity market that is already highly influenced by seasonal hydro power availability. The correlation between the seasonal patterns of wind, hydro, demand and prices has received little attention in the literature. In our approach, we separate daily deviations from the expected seasonal value, and show that for some locations it is the anomalies that have a more significant correlation with electricity prices than the seasonal patterns themselves. This indicates that the correlation results for anomalies from different wind sites can give valuable information on wind resource availability in critical periods of the year, such as dry seasons, and thereby enables identifying sites that can most optimally balance price volatility during these periods while potentially also maximising profits to investors. Even though the numerical results pertain to New Zealand, our methodology is applicable to any electricity system that utilises wind and hydro resources such as Chile, Colombia and several North American and Northern European jurisdictions. [ABSTRACT FROM AUTHOR]

Numerous studies assume that the price elasticity of electricity demand remains constant through the years. This, in turn, means that these studies assume that industrial consumers react in the same way to price fluctuations regardless of the actual price level. This paper proposes that the price elasticity of industrial electricity demand varies over time. The Kalman filter methodology is employed in an effort to provide policy-makers with more information on the behaviour of the industrial sector with regards to electricity price changes, focusing on the period 1970 to 2007. Other factors affecting electricity consumption, such as real output and employment, are also captured. The findings of this paper show that price sensitivity has changed since the 1970s. It has decreased in absolute values from -1 in 1980 to -0.953 in 1990 and then stabilised at approximately -0.95 which indicates that the industrial sector has experienced an inelastic demand. In other words, the behaviour of industrial consumers did not vary significantly during the 2000s. In the long run and as the prices increase, probably reaching the levels of the 1970s or even before, the industrial sector's behaviour might change and the elasticity might end up at levels higher than one (elastic). [ABSTRACT FROM AUTHOR]

The article looks at the energy consumption in Mexico with particular focus on households and analyzes their electricity and fuel demands in terms of households' income, rural and urban disposition, and their residents' age and gender. The author estimates energy consumption patterns per capita, based on his calculation of data from Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH) for 2008, concerning families' expenses on electricity, gas, and firewood.