Powering a sustainable electricity ecosystem
Making the grid more efficient with ML-powered electricity value ecosystem studio.
3 MINS READ
An electricity value ecosystem studio helps stakeholders in the power sector to make informed decisions, backed by comprehensive market research and predictions.
The machine learning-led simulation studio helps customers plan and strategize decisions using data modelling techniques and visualization.
It helps to increase revenue of power generating companies and reduce procurement costs for utilities in the sector.
It predicted saving nearly $2 million per annum for an Australian mining company through market participation.
A platform for sustainable energy management
The power sector is complex and layered.
With limited visibility into the value chain, stakeholders in the ecosystem, including plant operators, wind turbine owners, retailers, and prosumers, have a particularly tough time handling uncertainty in the demand and supply of electrical power.
Electric power companies have a defined need for competitive intelligence to make strategic and informed decisions. However, most decision-making tools in the electricity market are not comprehensive to meet the needs of all players in the market. Analytics is often restricted to a single or specific functionality.
TCS Research scientists have invented an electricity value ecosystem studio that functions as an interactive platform and offers holistic solutions to keep energy management sustainable. This machine learning-driven simulation studio, helps stakeholders to plan, strategize, and make insightful decisions based on data modelling techniques, visualization, and in-depth research into energy value networks.
A graphical representation of different stakeholder questions that are addressed through the platform.
As a decision-making tool, the invention can help stakeholders across the electricity value chain. As a case in point, it helps power generating companies increase revenue. It cuts power procurement costs for utility companies that buy energy from wholesale markets, which tells on the end user’s power bill. Here’s an example of how this plays out.
Saving close to $2M
A leading Australian mining company managing a 140-megawatt load, wanted its procurement costs to be cut down without violating existing contracts.
Our electricity value ecosystem studio first studied power optimization, load prioritization, and load analysis. It then used advanced data analytics and evaluated network charges and metrics to arrive at an estimated savings of nearly $2 million per annum that would be possible through market participation. The assessment helped the company make an informed pricing decision when purchasing from the market.
A smarter price bidding strategy
A French multinational oil and gas company sought to maximize its market trades.
In a two-sided electricity market, auctions offer better value to both buyers and sellers for the electricity traded. Price bidding is one activity that demands high predictive skills. Many traders lose out due to an inaccurate forecasting of where the market is headed.
Our invention offered the French company a ‘what-if’ analysis with multiple scenarios, given its range of abilities that includes integrating third-party analytic tools, offering generator selection (in case of a generating plant not being available due to maintenance), forecasting on market pricing, demand, or figuring out what is a more optimum energy type—wind or solar. All of this made it easy for the customer to arrive at an informed, evidence-based decision. The assessment helped the customer participate in the day-ahead as well as intraday market.
What the studio does
The electricity value ecosystem studio covers the power ecosystem comprehensively in terms of power generation, distribution, transmission, micro-grids, distributed energy resources, renewables, EV charging, and smart metering.
The platform is built on six parameters or building blocks.
The platform’s biggest advantage is its ability to foresee market trends and patterns. By providing valuable information on interaction rules (where different players in the ecosystem interact based on the information/estimation of market and other competitive players’ behavior), it helps a stakeholder visualize how the electricity environment will play out. It makes businesses future-ready, risk-proof, competitive, and open to newer opportunities based on intelligence.
It equips the customer to make an informed, stable decision in an environment otherwise fraught with fluctuations.