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Focus on grid balancing, optimal storage capacity and spatial distribution of power demand is needed.

The success of India’s net zero pledge by 2070 rests heavily on India’s successful energy transition in the power sector, as it is responsible for more than 50 per cent of emission.

So, India has gone all out to expand installed capacity of renewable electricity, with a bias towards solar. The report card indicates that there has been a sharp rise in the installed capacity of renewable electricity even though the energy mix of generated renewable electricity does not indicate any sharp spike. In fact, the divergence between generation and installed capacity of renewable electricity is becoming wider.

This trend needs to be reversed. A primary reason for this trend is the way our distribution companies enter into purchasing agreements with the producer of renewable electricity.

A distribution company usually does not insist on supply of power for 24 hours from the producer of renewable electricity but on purchasing their entire production even if it is limited to eight hours in a day — the general production hour of a typical solar-based power plant.

As a result, the risk of purchasing power for the rest of the time of the day lies with the distribution company, which is dependent mostly on fossil power for same. Barring the new Adani mega renewable power project, almost none of the renewable power companies has attempted to build in solar/wind hybrid/battery storage model for providing uninterrupted power for 24 hours.

If the purchasing agreement insist on buying power for 24 hours from a supplier, we would have seen more such hybrid power projects.

Grid balancing, transmission

Currently our fossil-based power projects are more or less evenly spread across India as coal/piped gas are by and large available all over India. Consequently, the transmission line of India along with substation has been developed accordingly.

On the contrary, the renewable power like solar is by and large being produced in a few States due to land constraint. The potential for wind energy is also observed to be concentrated in a few States. Thus, the existing transmission line and substations may not be able to transmit power over much longer distances.

Furthermore, unlike power from conventional sources, power from renewable sources always exhibits large variation in a day due to vagaries of nature (wind speed, sunlight, etc).

Thus, in other countries where the emphasis is on producing higher electricity from renewable sources, solar/wind capacity augmentation goes hand in hand with other sources like hydro power or particularly pumped hydroelectric energy storage (PHES) for load balancing.

PHES has emerged as one of the most important sources of hydroelectric energy storage used by electric power systems for load balancing. However, this does not seem to be in much favour in India. Only recently has India woken up to the grid balancing aspect and tenders are being floated for storage of electricity in batteries along with construction of renewable solar plant.

Integrated assessment model linked to power system model is a potential solution to further enhance energy accessibility and optimise the power generation cost by minimising the curtailment of renewable power through optimal introduction ofstorage capacity and location specific planning.

Mapping plan

Spatial mapping of available RE resources along with transmission and distribution network and mapping of demand can further help policymakers prepare an implementation plan for low carbon transition.

It plays a crucial role by ensuring energy through resource planning, optimising energy mix, infrastructure planning, policy formulation and economic analysis. In many EU countries, energy planning considers power infrastructure, network topology, and spatial distribution of power demand while planning for electricity transition.

Till now, probably all the bottom up energy models developed in the context of India do not take these into account. As a result, investment numbers generated out of these modelling exercises for energy transition may be off-target or infeasible. It is time a power system model for renewable electricity integration and energy transition analysis is developed in India.

Sanjib Pohit is Professor at NCAER. Views are personal.

The Indian data market remains in its infancy due to regulatory ambiguity, despite the global trend of enterprises monetising various types of data.

The potency of data becoming a critical asset is now a reality. Familiar phrases such as “data is the new gold” or “data is the new oil” underscore its value. In the growing pile of information, we need a new shovel to dig up gold.

The Internet of Things (IoT), Artificial Intelligence (AI), cloud computing (CC) and machine learning (ML) would leverage the utilisation of data. With data being generated at an unprecedented rate and quantity, its monetisation has also been in focus. It is the process of generating revenue or economic value from data assets. This can include selling or trading data to third parties or using it internally.

Data sharing and monetisation in India
Despite the global trend of enterprises monetising various types of data, the Indian data market remains in its infancy due to regulatory ambiguity. Just like elsewhere in the world, India is in the middle of a data revolution with the government being the largest repository of data. There have been several attempts to frame policies and frameworks.

In March 2012, the National Data Sharing and Accessibility Policy (NDSAP) was published with the objective of increasing the accessibility and facilitating easier sharing of non-sensitive data generated using public funds by various agencies of the government of India, for scientific, economic, and social developmental purposes. It excluded, among others, personal information, and data related to intellectual property rights such as patents, trademarks, official marks, and identity documents. In pursuance of this policy, the government, through the National Informatics Centre (NIC), set up the Open Government Data (OGD) platform to provide open access through the proactive release of data available with various ministries and departments.

Next was the Kris Gopalakrishnan Committee on Non-Personal Data Governance Framework (2020). The Committee suggested that non-personal data should be regulated to (i) enable a data-sharing framework to tap the economic, social, and public value of such data, and (ii) address concerns of harm arising from its use.

The Committee identified three purposes for Non-Personal Data Sharing—Sovereign Purpose (national security, legal purposes), Public Good Purpose (public good and benefits of society at large), and Business Purpose (sharing of non-personal data between two or more for-profit private entities). But the Committee also cautioned that current methods for anonymising data still leave individuals at risk of re-identification, as research has shown.

India’s first formal foray into monetising data was the formulation of the Draft India Data Accessibility and Use Policy (IDAUP) of February 2022. It laid down that every government ministry and department will identify non-personal datasets and classify them as open, restricted or non-shareable. It also lays down protocols for the sharing of non-personal datasets. The policy further specified the “pricing & licensing” process for high-value datasets (HVD) of the government, which have undergone value addition through defined pricing guidelines. To address privacy concerns, it suggested anonymisation tools be put in place and to include a “negative list” of datasets that will not be accessible to the public. However, this policy got scraped after facing criticism that monetisation of data would go against the principle of open government data.

In May 2022, the government released the revised National Data Governance Framework Policy, which did away with the idea of monetising data. It, inter alia, proposes to launch “non-personal data based India Datasets program and addresses the methods and rules to ensure that non-personal data and anonymised data from both government and private entities are safely accessible by research and innovation eco-system.”

Then, in Union Budget 2023-2024, the government announced that it will launch the National Data Governance Policy (NDGP) to enable access to anonymised dataset, and unleash innovation by startups and academia. It will aim to enhance citizen awareness, participation, and engagement with open data, increase the availability of datasets of national importance, identify suitable datasets for sharing, and improve overall compliance with secure data sharing and privacy policies and standards.

Meanwhile, the Digital Personal Data Protection (DPDP) Act 2023 was enacted with the objective to “provide for the processing of digital personal data in a manner that recognises both the right of individuals to protect their personal data and the need to process such personal data for lawful purposes…”. In case of any personal data breach, the Data Protection Board of India (DPBI) will be responsible for looking into the matter. The body is supposed to inquire into the breach and impose penalties. However, “data monetisation” as a concept and dealing with the associated privacy concerns has not been specifically spelled out or defined under the DPDP Act.

Need for threadbare approach
Data is one of the most valuable intangible assets. By leveraging it, India can drive innovation, enhance productivity, and address societal challenges across various sectors. Data has grown to be an important resource and services driven by it would be the next thing. It can also provide useful inputs for policy formulations and assist government agencies in identifying issues at the granular level.

The sovereign authority commanded by the government enables its agencies to collect vast amounts of data, with little hesitation or reluctance from the public in sharing information. Hence, data collection cannot be solely driven by profit motives. Security and privacy concerns require serious and adequate attention.

The overall legal framework should include adequate, stringent and well-balanced provisions. The lesson learned from the scrapping of the government’s policy, which allowed private entities to access the vehicle registration databases Vahan and Sarathi, and the Indian Railway Catering and Tourism Corporation’s (IRCTC) roll-back of a tender for hiring a consultant to monetise its passenger and freight customer data should be kept in mind. With the advancement in AI models, the possibility of “de-annonymisation” or “triangulation” or matching the data with other available databases with the ultimate aim to misuse is now becoming a greater possibility and threat. Another issue that needs equal attention is the possibility of data storage systems and networks being hacked.

India’s cautious approach to data sharing and monetisation reflects the need for nuanced strategies amid rapidly evolving technological landscapes. It is becoming more apparent that a ‘one size fits all’ approach will not work. It is crucial for the government to address key challenges related to data privacy, ownership, quality, and standardisation in a threadbare manner.

Dr Palash Baruah is Associate Fellow at National Council of Applied Economic Research (NCAER), New Delhi and DL Wankhar is a retired officer of the Government of India. Views are personal.

Affordable hospital care requires health-care financing reforms that go beyond price regulations.

Benchmark for pricing

In an unregulated market-driven scenario, health-care providers focus on profit through higher prices and overprovision of care (supplier-induced demand). One potential solution, “yardstick competition”, involves regulatory authorities setting benchmark prices based on market observations. However, this approach faces challenges in India due to diverse patient profiles, unreliable price data, and weak regulatory frameworks. Relying solely on competition from government hospitals is insufficient due to long wait times, perceived service quality issues, and patient information gaps, perpetuating the risk of supplier-induced demand.

As the Court observed, pricing-related discussions must start with a benchmark for price determination. Standard treatment guidelines, or STGs, can help establish relevant clinical needs, the nature and extent of care, and the costs of total inputs required. STGs can address confounders that account for varying levels of care for various hospital procedures while ensuring clinical autonomy to respond to individual needs. Consequently, it enables valuing health-care resources consumed for the precise cost of multiple procedures.

Given limited regulatory capacity, STG formulation and adoption require that providers’ revenues are tied to fewer payers. Providers must rely on reimbursements from pooled payments, covering most of the population with low out-of-pocket (OOP) payment levels. With government support, payers and providers could agree on pricing that provides a reasonable and sustainable surplus over and above the input costs.

However, this would be hindered if providers could access markets with OOP payments as an alternative or add-on to reimbursement payments. Several countries have accomplished this difficult feat through coordinated health-care purchasing reforms, highlighting that pricing issues are health systems challenges rather than law-and-order problems.

In India, over half the total health expenditure is OOP. The other half comes from a multitude of publicly and privately pooled resources. The private sector is predominantly composed of small-scale providers. Even if rates are standardised, their implementation will be uncertain. Enforcement mechanisms for adherence to prescribed rates remain unclear, raising questions about the feasibility of such regulatory measures. What if providers do not adhere to the prescribed procedure rates, much like they have resisted the rates in various health schemes?

Weak implementation

Command-and-control regulations through pecuniary measures such as price caps can swiftly influence actors’ behaviour by making them follow the pronouncements. However, when enforcement mechanisms are weak, these effects are temporary because the overall environment remains unchanged. The suggested measures face enormous enforcement challenges. Only 11 States and seven Union Territories have notified the Clinical Establishment Act, and its implementation remains weak, with little or no evidence about the impact on affordability, care quality, and provider behaviour.

Similar design and implementation capacity constraints have hampered the effective adoption of the National Pharmaceutical Pricing Authority’s decision to cap the prices of stents and implants since 2017 and of the many directives that mandate doctors to prescribe generic medicines.

Rate standardisation, through capped prices, may not address the fundamental problem of stakeholders’ misaligned incentives. A comprehensive health financing reform strategy informed by robust and ongoing research on appropriate processes for formulating and adopting STGs must be in place, without which the actual pricing can be manipulated and justified in any manner. For example, hospitals with lower average revenue per bed can push their rates higher by appealing to their better care quality. Without STGs, it will be nearly impossible to verify such claims objectively.

Limited data

The Pradhan Mantri Jan Arogya Yojana and the Department of Health Research have made significant strides in developing STGs for common conditions and adopting a comprehensive costing framework. Efforts are also ongoing to create an Indian version of Diagnostics-Related Groups (DRGs). Although the insurance industry initiated STGs for hospitals in 2010, progress was hindered by a lack of representative and accurate costing data due to limited participation from private hospitals.

This judgment is an opportunity to create effective processes to solve a major health system problem. Rate standardisation policies must be feasible, easily implementable, and follow established price discovery practices. Future efforts must build on previous and ongoing health financing reforms, address anticipated challenges, and ensure broader stakeholder participation.

Arun Tiwari is a Fellow at the Centre for Health Policy and Systems (CHPS), National Council of Applied Economic Research. Sumit Kane is a professor at the University of Melbourne and Centre for Health Policy and Systems (CHPS), National Council of Applied Economic Research. Ajay Mahal is a professor at the University of Melbourne and Centre for Health Policy and Systems (CHPS), National Council of Applied Economic Research.