Enhancing Market Agility Through Accurate Price Indicators Using Contextualized Data Analytics

Abstract

The volatility of the price of power being an inherent characteristic of the Electricity Trading Market, Utilities need to address this volatility strategically influencing key operational decisions in the day ahead, spot market, wholesale market, etc. The latest experience of Power Utility Ecosystem involved in the trading business while dealing with market-driven uncertainties, face major challenges introduced due to adaptation of distributed energy recourses (DER) at a significant percentage of penetration into grid. Utilities across the globe, while embarking on the green energy path, rely on the advanced digital enablers in increasing the visibility of DER penetration in achieving the Net Zero Carbon goal. The key influencers to price volatility being random, unforeseen, the accurate price-forecasting is always a very important differentiator for Utilities in taking up market-driven decisions, balancing the grid, and maximizing portfolio expectations. Electricity Market Operators and Electricity eco-system across the globe, face challenges in view of inaccurate predictive models, creating an impact on market participation, frequency control, dispatch strategies, scheduling downstream decisions, negative prices, and other techno-commercial implications. The potential of data analytics tools can be acknowledged to assess and harmonize data of load demand, generation availability, infrastructure constraints, power flow constraints, market constraints, double sides or single-sided auction bids, etc. The data-driven insights would enable Utility to unlock the market corridors, build flexibility of participation, accommodating a greater number of business players, increasing market agility, and best cost of power to the end customer. This chapter aims to present the global challenges of Power Utility belonging to electricity trading business in developed countries like USA, Europe, Australia, UK geo and how the blend of the tool with data and AI can empower the decisions of utility on keeping tradeoff between the profit, revenue, and risk in view of the supply chain, changing generation mix, consumption and load patterns, regulatory compliances and innovation and incentivization at customer engagements at the downstream of the Utility value chain.