An efficient bidding strategy for selecting most economic horizon in restructured electricity market with hybrid generation and energy storage

In the era of deregulation, constant efforts are being targeted towards the better power services by improving reliability, competitive power price, reduction of market power, and many more. The task of incorporating renewable energy sources while profit maximization becomes quite challenging. The uncertainty associated with them brings about a great deal of investment risk. This paper proposes a method for strategic bidding that not only helps in profit maximization but also keeps the risk factor under check. Despite using non-conventional energy; profit can still be maximized. The proposed approach is based on the Discrete-Time Markov Process (DTMDP) which helps to identify the most profitable economic zone for bidding in the power market while using hybrid generation. The system comprises of conventional and wind generation along with energy storage system. The DTMDP algorithm helps to mitigate uncertainty by learning from past scenarios. The past scenarios are hybrid generations without ESS. The proposed approach compares the present horizon with the past and decides whether to store or to dispatch energy from ESS. Any changes in the past scenario will directly impact the decision taken in the present horizon. Depending on the action taken reward is calculated. To determine the probabilistic wind generation Weibull probability distribution function has been used. The risk of each horizon has been calculated by using CVaR as risk assessment tool. The overall profit along with CVaR rating helps to decide the most profitable horizon for biding. Modified IEEE 14 bus system has been used for the case study to prove the efficacy of the proposed method.