The presence of consumers able to respond to changes in wholesale electricity prices facilitates the penetration of renewable intermittent sources of energy such as wind or sun power. We investigate how adapting demand to intermittent electricity supply by making consumers price-responsive - thanks to ...
PETER M. SCHWARZ [*] Many utilities are offering real-time pricing (RTP) to their large...doi:10.1007/bf02298399Taylor, Thomas N.Schwarz, Peter M.Atlantic Economic SocietyAtlantic Economic JournalT. N. Taylor and P. M. Schwarz 2000, "Advance Notice of Real-Time Electricity Prices," ...
In recent years, extreme electricity prices have occurred with greater frequency and magnitude. Accurately predicting extreme electricity prices is of great interests to market participants. This paper aims to forecast real-time electricity prices for the next 24 hours for the Houston load zone in Ele...
Data centers constitute 1.1-1.5% of total electricity usage in the world. Taking a more informed view of the electrical grid by analysing real-time electricity prices, we set the foundations of a grid-conscious cloud. We propose a scheduling algorithm that predicts electricity price peaks and ...
Adoption of real-time electricity pricing %u2014 retail prices that vary hourly to reflect changing wholesale prices %u2014 removes existing cross-subsidies to those customers that consume disproportionately more when wholesale prices are highest. If their losses are substantial, these customers are ...
Under the background of smart grid’s real-time electricity prices theory, a real-time electricity prices and wireless communication smart meter was designed. The metering chip collects power consumption information. The real-time clock chip records curr
We study the e ect of energy-storage systems in dynamic real-time electricity markets. We consider that demand and renewable generation are stochastic, that real-time produc- tion is a ected by ramping constraints, and that market players seek to sel shly maximize their pro t. We disti...
Scalable, Real-Time Electricity Demand Response Optimization in the Smart Grid Intel Science Talent Search November, 2013 1 Abstract With the growing smart grid effort, and the fine-grained electricity demand data that comes with it, utility companies have gained the resources to implement Demand ...
In the field of load forecasting, a series of factors such as environmental factors, real-time electricity prices, and special dates present different characteristics. To extract the important factors affecting the load better, the depth and scale of the network are adjusted adaptively. In this pap...
2020, IEEE Transactions on Industry Applications Using real-time electricity prices to leverage electrical energy storage and flexible loads in a smart grid environment utilizing machine learning techniques 2019, Processes View all citing articles on ScopusView...