This project was undertaken as a part of seminar requirement under the guidance of Prof. Ankur Kulkarni. With growing dependence on technology, there is an ever increasing demand for electricity. Not only has this burdened generation units in terms of large power demand but also in terms of its highly irregular demand profile. This has ensued various pricing policies by utilities to mitigate the run time cost of power generating units. In developed countries, one such scheme utilizes the concept of dynamic tariff. During peak hours, cost per unit of electricity is kept high, and during off-peak hours tarrifs are brought down to moderate the energy demand profile.
The project was a literature survey of several game theoretic models to study the benefit of coalition for electricity consumers under different pricing models. Moreover, focus was restricted to 4 published articles by a research group at University of California, Berkley.

One way to minimize loss is to decrease individual's exposure to real time market. This can be easily achieved by an investment on battery storage. Size of battery is identified by solving an optimization problem to minimize expected cost in long run. It turns out that investing on a shared battery resource is better than investing on individual battery storage, therefore, highlighting the benefit of coalition formation.
The presentation also discusses other models with different objective functions, and improvement in individual's benefit under coalition formation.