Indian agriculture sector poses challenges for three other sectors in India: energy, environment, and economy. The sector consumes 17 per cent of the total electricity in India (Ministry of Statistics and Programme Implementation 2021) and continues to be a heavily subsidised segment for the distribution companies (discoms), receiving 75 per cent of the total electricity subsidies (Aggarwal, et al. 2020). Indian discoms are already burdened with retail tariffs being much below the average cost of supply² (ACoS),³ delays in subsidy disbursements, and poor collection and billing. Further, they realise very poor revenue from agricultural consumers, which adds up to their financial crunch. There are over 30 million agriculture pumps installed in India, deployed primarily for irrigation purposes. Around 10 million pumps (Ministry of New and Renewable Energy 2019) in India run on diesel and emit around 60 million tons of CO2 .⁴ Solarising the dieselbased irrigation, for instance under (PM-KUSUM-B),⁵ translates to a latent demand of 8.25 GW (Standing Committee on Energy, 17th Loksabha 2021).⁶ The remaining pumps mainly use grid electricity, which is dominated by thermal generation (75 per cent of total generation),⁷ adding to air pollution and global warming. Notably, the sector employs around 59 per cent of India’s working population (Food and Agriculture Organisation 2017), with an abysmal per capita income of around INR 6,427 a month, leaving no room for savings (National Sample Survey Office 2013).

Solarising agricultural power consumption can address the challenges posed to three other sectors highlighted earlier. Solar tariffs lower the cost of electricity supply to agricultural consumers, reducing the gap between ACoS and the retail tariffs. This gives some relief to state governments that operate in a limited fiscal space. Commercial and industrial (C&I) consumers also benefit from a potential reduction in cross-subsidy quantum. Also, solarising pump usage will reduce the carbon emissions from the sector significantly. Although water consumption at the farm level may not be altered,⁸ solar feeders contribute to the conservation of scarce national resources by eliminating the need for water required in thermal generation: a typical thermal plant consumes 3.7 litres of water to generate 1 kWh of electricity post-adjustment of transmission and distribution (T&D) losses. Farmers can also enhance their income by leasing out land to the project developers or selling solar power to the discoms.

Figure 1 Retail tariffs for agriculture consumers in Delhi are much lower than the average cost of supply

Source: Authors’ adaption from DERC tariff orders

Given the multitude of benefits of solarising agriculture, the Government of India launched the Pradhan Mantri Kisan Urja Suraksha Evam Utthaan Mahabhiyan (PM-KUSUM) scheme in 2019, intending to reduce the subsidy burden on agriculture consumption, contribute to India’s nationally determined contributions (NDC), and increase farmer’s income. The scheme has three components—A, B, and C. Under component A, renewable energy projects with a combined capacity of 10,000 MW, with each project between 500 kW and 2 MW capacity, will be set up by groups of farmers and project developers. The power will be bought by discoms at a feed-in tariff. Discoms have also been given the option to own and operate these solar plants in case farmers cannot raise equity. Discoms are given INR 0.40 per kWh or INR 6.6 lakh per MW of installed capacity for the first five years from the commissioning date of the projects as a performancebased incentive (PBI). Discoms also realise system-level benefits such as avoided power purchase cost, RPO compliance, and avoided T&D losses. Additionally, there are a few state-level schemes for the solarisation of agriculture such as Mukhyamantri Saur Krushi Vahini Yojana in Maharashtra and Agriculture cum Solar Farm Scheme in Delhi. In this brief, we analyse different ownership structures and their impact on the discom revenue and farmers’ income through a case study approach. This issue brief covers the component A of the PM-KUSUM scheme and the Agriculture cum Solar Farm Scheme by the Government of Delhi.

We used data from the Tata Power Delhi Distribution Limited (TP-DDL) to assess the techno-commercial viability of solar agriculture micro-grids using cost– benefit analysis. The TP-DDL shared the relevant data in FY19–20 for the study.

Case study of agriculture consumers in north Delhi

We studied the impact of solar micro-grids for different business models in TP-DDL licensee area, which supplies power in north and north-east Delhi. The share of agriculture in total sales is abysmal (DERC Tariff Orders FY15-FY21) (i.e., 0.17–0.20 per cent)⁹ , which leads to revenue loss for the discom. The quantum of agriculture sales has remained almost stagnant between 12 and 14 MU over last few years and so has the sanctioned load, which is about 28 MW. The tariff design in Delhi is similar to many other states. Agricultural consumption is heavily subsidised, as electricity tariffs are much below the ACoS. In fact, the retail tariff for the agriculture category fell by almost 80 per cent in 2019 and has remained unchanged. Insights from the case study could help other states to adopt strategies and business models for the uptake of solar in the agriculture sector. The power is supplied primarily for tube-well irrigation, threshing,¹⁰ and kutti cutting.¹¹ Figure 1 shows the trends in agriculture sales, retail tariffs, and the ACoS.

The case study assesses the techno-economic impact of solar micro-grid on the farmer’s revenue, the discom business, and on feeder load profile in Narela district (zone 514) in North Delhi.¹² We compute the levelised cost of solar generation (LCoE) using the discounted cash flow method under four ownership models described in section 2. The assumptions for LCoE calculations are shown in Annexure A. We also quantify broader system-level benefits of solar plants injecting power into the selected feeders of the discom (in INR per kWh and in INR lakh). These benefits are computed over the lifetime of the solar plant (25 years) and brought to present value terms. The benefits are indicated in Figure 6. Since the analysis is done for FY 19–20, when the floor price of renewable energy certificate (REC) was set to INR 1 per kWh and when the market was functional, we have used INR 1.12 per kWh as the REC cost incurred on TP-DDL based on our analysis of the tariff order. We then compare the system-level benefits with the cost of solar generation, to arrive at net benefits and reduction in the cost of supply (INR per kWh and INR lakh) spread over 25 years. The monetary benefits to farmers are also estimated under all ownership cases.

Figure 6 Costs and benefits to the discom of a solar plant connected to the agriculture feeder

Source: Authors’ analysis

The solar micro-grid of size 1 MW has been considered for our techno-economic analysis. The plant is connected directly to the feeder substation of the licensee and injects power into the grid. The analysis has been carried for two demand scenarios: (i) when the agriculture load is supplied power only during daytime (6 a.m. to 6 p.m.) and (ii) when the load is supplied power round the clock. Figure 7 shows the schematics of solar micro-grid. As in many states, the agricultural load is fed on roaster basis—daytime supply on some days/week and night time supply on the other days. We have considered the impact of time of pump usage on the net benefits to the discom and reduction in cost of supply to the farmers by the discom. Figure 8 shows the load profile of a sample distribution transformer (DT) in the TP-DDL region.

Figure 7 Schematic representation of a typical solar feeder micro-grid

Source: Prayas Energy Group (Solar Feeder)

Figure 8 Agriculture load on a selected DT in TP-DDL licensee area

Source: Authors’ adaption from TP-DDL data

Learnings from economic viability assessment

In this section, we present the economic viability of four business models: farmer-owned system, third-party owned-owned system selling power to the discom, thirdparty owned systems selling power only to government entities, and the discom-owned system. We also test the impact of time and duration of the agricultural load and system size on the economics of the solar plant. The impact on farmers’ income under four business model is also analysed in the section.

Figure 9 Farmer-owned system is the cheapest way to generate power

Source: Authors’ analysis Note:

Values in blue font indicate ‘LCoE’

Figure 9 compares the LCoE for different business models. For farmer- and discom-owned systems, the cost of procuring components such as modules, inverters, and wires would be higher than for third-party owned systems because the former would be procuring them at the market price while the latter would do so at wholesale quantum, giving cost advantage for the third-party owned systems. Additionally, developers can raise capital at more attractive interest rates due to better credit rating compared to farmers and the discoms. Therefore, comparatively, the cost of debt is least in third-party owned systems. The developers operate their businesses on a thin margin due to sharp competition and thus give lowest return on equity compared to other ownership structures. Return on equity for the discoms and the farmers would be based on the regulated return on equity based on prevalent feed-in tariff and thus appears to be higher than in the developer-owned system. Yet, farmer-owned models are likely to fetch the lowest levelised tariff as the lease rent for other models increase the tariff by around 17–28 per cent (adding about 0.7 INR/kWh). The savings on land lease offsets the increase in input prices and other financial costs, making farmer-owned system cheapest in INR per kWh terms among the business models.

Figure 10 Farmer-owned system supplying agriculture load in daytime gives maximum reduction in cost of supply in the first year

Source: Authors’ analysis

Note: The values in blue font indicate ‘Net reduction in cost of supply’.

Figure 10 shows the reduction in cost of supply (CoS) to agricultural consumers in the first year across three business models and for two load supply durations: day time and round-the-clock supply. Benefits like performance-based incentive (PBI) and avoided REC purchase (or avoided RPO penalty cost) are related to annual generation, which remains the same across all the cases. The variable cost of the marginal generator that supplies power during daytime is observed to be higher than the variable cost during night time.

The discom could save on power purchase expenses by shifting the supply during daytime. The highest reduction in CoS is seen in farmer-owned systems, as they yield lowest solar tariff among other ownership structures. Farmers can earn additional revenue by selling power to discoms. However, system ownership requires capital investments, debt servicing, and O&M expenses, which reduce net income for the farmers.

Figure 11 compares net benefits for the discom under three business models and for different supply durations over the period of 25 years. The discom could save more on power purchase expenses and meet the RPO targets if the agriculture load is supplied during daytime across all the business models. The average power purchase cost incurred to the discom during daytime is observed to be higher than the average power purchase expenses incurred for round-the-clock procurement. Avoided REC purchase cost and PBI are directly linked to the solar generation, and therefore their contribution to the net benefits remains the same (INR 0.56 per kWh) across all the business models and supply durations. In absence of functional REC markets, the avoided REC component can be treated as avoided RPO penalty cost. Our analysis considers INR 1.12 per kWh as avoided RPO penalty cost. Farmer-owned systems give maximum net benefits to the discom, as they yield lowest tariffs across three business models.

Figure 11 Discom realises highest net benefits over the lifetime when a farmer-owned system supplies the agriculture load during day time

Source: Authors’ analysis

Note: The values in blue font indicate ‘Net benefits over the lifetime’.

Figure 12 The discom incurs revenue loss under agriculture cum solar farm when the developer sells power to the government entities through net metering

Source: Authors’ analysis

Note: The values in blue font indicate ‘Net revenue loss’.

Under Agriculture cum Solar Farm Scheme, the developer sells electricity at a competitively determined tariff to government entities under RESCO arrangement. The entities such as Delhi Jal Board and Public Works Department reduce their electricity bills through virtual net metering, as their commercial rates are higher than the solar tariffs. This results in a net loss to the discom (INR 1.56 per kWh) as it loses on premium sales (Figure 12).

The scheme also mandates free electricity up to 6,000 kWh per MW per year to the farmers, which reduces subsidised sales of the discom and gives a net benefit of INR 0.30 per kWh similar to the simple arrangement where the discom signs a PPA with the developer and buys power at a competitively determined tariff. It is noted that the avoided power purchase expenses, RPO compliance costs, and PBI are linked to solar generation and thus remains the same across different cases considered.

The scheme provides for INR 8,333 per month per acre to the farmers as rent, which would escalate at 6 per cent a year, and 6,000 units of free electricity a year from the solar plant in case the farmer leases land. This means that the farmers could deploy their equity for other productive purposes in the farming activities. As seen in Figure 13, the income from land leasing is seen six times more than the income from system ownership. Therefore, land leasing is a more beneficial proposition for farmers to earn additional income without much effort.

Figure 13 System ownership is less beneficial to farmers over the 25 years

Source: Authors’ analysis