The Chinese government began to implement an increasing block tariff (IBT) nationwide in the residential sector in July 2012. Although there have been a number of studies on the impacts of an IBT, knowledge about IBT design is still limited, particularly how to determine the electricity volume for the first block of an IBT scheme, which is intended to protect those households with low levels of...

We characterize the optimal regulatory policy to promote demand response in the electricity sector. Demand response arises when consumers reduce their purchases of electricity in times of peak demand, when the utility’s marginal cost of supplying electricity is relatively high. The optimal policy differs systematically from the policy in the U. S. Federal Energy Regulatory Commission’s (FERC’s)...

Forecasting electricity consumption is one of the most important operational issues in order to the use facility systems and power sources optimally. Electricity demand forecasting process will ultimately have an important role in the economic and security of the energy operating system. The objectives of this research are to forecast long-term electricity demand for 2011-2022 and to provide ma...

this paper proposes a stochastic framework for demand response (dr) aggregator to procure dr from customers and sell it to purchasers in the wholesale electricity market. the aggregator assigns fixed dr contracts with customers based on three different load reduction strategies. in the presented problem the uncertainty of market price is considered and the risk of aggregator participation is ma...

Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is ...

Main challenges within the energy system of tomorrow are more volatile, less controllable and at the same time more decentralized electricity generation. Furthermore, the increasing research and development activities on electric vehicles (EV) make a significant share of electric vehicles within the passenger car fleet in 2030 more and more likely. This will lead to a further increase of power ...

This paper aimed at estimation of the per capita consumption of electricity in residential sector based on economic indicators in Iran. The Genetic Algorithm Electricity Demand Model (GAEDM) was developed based on the past data using the genetic algorithm approach (GAA). The economic indicators used during the model development include: gross domestic product (GDP) in terms of per capita and re...

Electricity markets are systems for affecting the purchase and sale of electricity using supply and demand to set energy prices. Electricity can be traded in organized markets or by negotiating forward bilateral contracts. Demand response (DR) refers to participation by customers in electricity markets, seeing and responding to prices as they change over time. Customers may adopt several basic ...

Consumption of energy is influenced by a multitude of factors. Beyond factors determining the demand for a specific energy service, characteristics of and attitudes to the energy product delivering the service can also strongly affect this demand. Attributes of electricity which may influence the demand for electricity services include its cost, its environmental impacts, and the social/politic...