Rapid expansion at smart grids on conjunction with IOT devices has resulted in security flaws, allowing attackers to launch attacks for variety of reasons. IOT has played major role to control electric application anywhere from the world. Number of devices are now connected with it. It can be applied to control variety of electric application like TV, AC, geyser etc. Wireless technology can be used to control all devices where all devices are centrally connected to IOT. The basic idea of cyber risk management is to identify the type of the risk and to propose a strategy to handle the risk according to its type. Different author has proposed different method to analyse and manage cyber risk present in the power grid system. Author has used various methods and algorithms like probability response model, Ensemble prediction algorithm based on Time Series (EPABT), characteristics of protection system product, Multiarmed bandit approach and Integration of Electricity and Gas System (IEGS) method. The probability response model works according to response values of the particular risk. Probability of the risk may vary according to its type. Various methods and algorithms are used to calculate and analyse the risk present in the power grid system. EPABT works according to log types. Characteristics of protection system product get varied as per their use. Multiarmed bandit approach is worked according to the attack behaviour. The IEGS method mainly focus on the false data injection attack. This method is useful against malicious cyber-attack while using the renewable energy. After analysing the various algorithm and approaches it is found that every approach has its own advantages and disadvantages. Hence research is needed to develop a system which could be used to manage the risk in power grid system with more accuracy © 2021 IEEE.