Standardized Dynamic Pricing Model for Cloud Services in Smart Cities

A smart city is a new concept of cities that apply the new generation of information communication technologies (Smart ICT), such as the Internet-of-Things, cloud computing, big data, to improve and manage the planning, construction and smart services of cities.

Developing Smart Cities can benefit synchronized development, industrialization, information sharing, urbanization and agricultural modernization and sustainability of cities development. The utility power system in smart City is highly energy and resource efficient, and is increasingly powered by renewable energy sources; it relies on integrated and resilient resource systems, as well as insight-driven and innovative approaches to strategic planning. The application of information and communication technologies is commonly a means to meet these objectives.

One of the major components of smart cities’ utility power system is the smart grid. The smart grid is an electrical grid including a variety of operational and energy measures such as smart meters, smart appliances and allows the integration of various power generation resources. With the increasing concerns about climate change the interest in integrating renewable resources into the smart grid increases. As these renewable energy sources might be highly intermittent in nature and often uncontrollable, they could produce a significant challenge for the reliability of the grid. It is therefore a challenging task to guarantee that the power demand, load and power generation remain balanced; stressing the need for standardized power allocation and dynamic pricing schemes.

As a step into this direction, we study dynamic pricing strategies for brokering, which will be implemented on the cloud service, on the based upon data collected from smart meters to help the users make the best selection with the energy resources from different energy retailers. In this dynamic pricing scheme, more than one energy retailer is considered and for each retailer, the price for the users can be adjusted dynamically depending on the current energy demand and prices offered by the other retailers in each region; in order to achieve the highest individual or combined revenue.

The users’ energy demand changes with the price to maximize their individual utility, and users might choose different retailers based on the provided prices. The brokering will choose the lowest cost of energy resources based on clients’ energy usage demand in real time. Dynamic pricing aims at reducing the overall energy consumption, the capacity of end use customers to change their electricity usage from their normal or current consumption patterns in response to market signals is mainly about shifting consumption to a different point in time. Furthermore, during the analysis, we have come to know that standardization in the area of metering and billing lags behind research.