Price spikes are a common phenomenon in deregulated modern electricity markets. They usually occur during periods of high energy demand, often aggravated by maintenance events, power plant closures, or limitations of electricity storage. The patterns of spikes in different energy markets, including their frequency, duration, magnitude, and seasonal, weekly, and daily cycles, are critical for energy option valuation and trading. Accurately forecasted distributions of electricity prices must include the spike component, which significantly impacts option pricing and optimal trading strategies. The definition of spikes and their detection criteria in spot electricity prices are crucial for effective forecasting. We define spikes as significant short-term changes in the distribution of spot electricity prices. Sequential and retrospective methods are proposed for detecting and estimating spike regions. We apply a parametric transient change-point approach to detect occurrences of spikes and to estimate their duration and magnitude under the assumption of an autoregressive process AR(1) of detrended spot log-prices, with distinct parameters under the normal and spike modes. As an illustration, we apply the proposed methods to detect and analyze electricity price spikes in the open-source Nord Pool Spot Market data, including day-ahead spot electricity prices in Denmark and its neighboring countries.