Recent studies show that the fast growing expansion of wind power generation
may lead to extremely high levels of price volatility in wholesale electricity
markets. Storage technologies, regardless of their specific forms e.g.
pump-storage hydro, large-scale or distributed batteries, are capable of
alleviating the extreme price volatility levels due to their energy usage time
shifting, fast-ramping and price arbitrage capabilities. In this paper, we
propose a stochastic bi-level optimization model to find the optimal nodal
storage capacities required to achieve a certain price volatility level in a
highly volatile electricity market. The decision on storage capacities is made
in the upper level problem and the operation of strategic/regulated generation,
storage and transmission players is modeled at the lower level problem using an
extended Cournot-based stochastic game. The South Australia (SA) electricity
market, which has recently experienced high levels of price volatility, is
considered as the case study for the proposed storage allocation framework. Our
numerical results indicate that 80% price volatility reduction in SA
electricity market can be achieved by installing either 340 MWh regulated
storage or 420 MWh strategic storage. In other words, regulated storage firms
are more efficient in reducing the price volatility than strategic storage
firms.Comment: 8 pages, 5 figure