introducing micro markets for electricity in india ...€¦ · india is one of the fast growing...

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Introducing micro-markets for electricity in India: Improving reliability as well as

sustainability

Pradyumna C Bhagwat*and Laurens de Vries

Faculty of Technology, Policy and Management. Delft University of Technology. Jaffalaan 5, 2628 BX, Delft, The

Netherlands

*Corresponding author, mail: [email protected]; Telephone: +31 152 783 963.

ABSTRACT

In this research we propose a micro-market for providing electricity during load shedding that

is easy to replicate and analyze the possible incentive for investment in distributed generation from

such a system. The micro-markets make investments in diesel and solar energy based distributed

generation attractive, even if these distributed generation systems depend exclusively on the micro-

market for revenues and have no other source of income or use. We also can conclude that the

consumer would strongly benefit by avoiding outages. A hybrid policy instrument such as the

micro-markets for electricity can lead to improvement in electricity adequacy for industrial as well

as residential sector.

KEYWORDS: distributed generation, electricity markets, generation adequacy.

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1. Introduction

India is one of the fast growing economies in the world with an ever-rising growth in demand

for electricity from both the industrial as well as residential sector. The per capita power

consumption in India has grown from 16.3 KWh per capita in 1947 to 1010 KWh per capita in 2015

(CEA India, 2015). However, in most regions, the private and government investment in generation

capacity has not been able to keep up with the demand growth. This can be observed from an

expected peak load deficit of 2.1% - 2.6% in fiscal year 2015-16. Furthermore, as demonstrated by

the power outage in 2012, that left roughly 300 million people without electricity, the electrical

infrastructure in India is unreliable. These issues have led to debilitating load shedding across the

country, especially in the rural areas. These outages negatively affect industrial and agricultural

productivity and also the comfort of common citizens. Due to this, many consumers resort to

installation of back up capacity. This back up capacity mainly consists of diesel generators.

According to Central Electricity Regulatory Commission (CERC), it is estimated that the total

decentralized diesel generator based installed capacity in India is in the range of 90 GW as of 2014

(CERC India, 2015). A comparison of the cost of electricity from such diesel generators in the

range of 15 - 17 ₹/KWh to a retail price (industrial consumers) estimated between to be between 7

– 9 ₹/KWh, indicates a substantially high willingness to pay for electricity. CERC estimates a

Value of lost load (VOLL) of between 34 ₹/KWh to 112 ₹/KWh for India.

India’s electricity sector has been studied in detailed (Lamb, 2006; Sharma et al., 2005) and

research has been conducted on possible pathways for power sector reforms in India (Singh, 2006;

Srivastava and Shahidehpour, 2002). Many studies have also been conducted regarding the possible

technological alternatives for distributed generation in India (Alanne and Saari, 2006; Narula et al.,

2012; Singh and Parida, 2013). However, very little research has been conducted on utilizing

innovative institutional mechanisms for efficient utilization distributed generation to provide

adequacy in India. In this study, we propose a micro market for electricity that operates during

hours supply when supply is insufficient (load shedding hours). The distributed back-up capacity is

integrated into the system for supply and further combined with capacity subscriptions on the

consumer end in order to improve adequacy.

In Section 2, we describe the proposed concept in detail. We analyze the possible implication

of applying such a concept in a case study in section 3 followed by conclusions in section 4.

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2. Concept description

Load shedding in India is generally planned and takes the form of rolling blackouts. This

means that at a fixed time of the day and for fixed number of hours, particular regions would face

blackouts, while other regions would receive electricity. In this paper we propose creation of a

micro-market to trade distributed back-up generation capacity between regions with and without

load shedding.

As described in the introduction, a large section of India depends upon off-grid or distributed

generation for catering to their electricity needs during shortage hours. Currently this generation

mainly consists of diesel generation sets and captive generation in the industrial sector. Usually,

when electricity from the grid is available, these generation systems remain idle due the high cost of

generation as compared to grid electricity. It is conceivable that owners of these generators would

supply electricity by running these units for additional hours in order to generate revenue. Some of

the generation capacity may also come from excess electricity produced by captive generation units.

The supply aggregators would purchase electricity from these distributed electricity generators and

trade it the electricity market.

With the term ‘micro-markets’ we refer to localized electricity markets within small

geographic regions. These regions may be groups of villages or neighboring districts. We propose a

structure in which back-up capacity from outside the area of load shedding is made available at a

price to the area with load shedding. The price for this capacity is set by creating micro-markets for

trading electricity between regions with different load-shedding timings. This market would operate

only any hours with load shedding.

A schematic description of the proposed mechanism is presented in Figure 1. The illustration

provides an overview of the mechanisms and the relationships between various actors involved in

this system. The five key stakeholders that would directly or indirectly participate in this

mechanism are the government, market regulator, aggregators, power generators and consumers.

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Figure 1: Schematic representation of the system

Aggregators are the entities that would trade on the micro-markets. There can be three types

of aggregators: 1) demand-side aggregators 2) supply-side aggregators 3) combined aggregators.

The primary function of a demand-side aggregator is to buy electricity from the market and

sell it to customers. The consumers may consist of industry or individual households in the area

with a black out, which purchase electricity from these demand-side aggregators depending upon

their electricity requirement during this period.

The demand-side aggregators sell energy to the consumers based on their willingness to pay.

They are free to decide their own tariff structure. An example of a tariff structure that a consumer

could have is the option of either paying a flat price per unit of electricity or a tariff linked to the

market-clearing price. The aggregator could use capacity subscriptions (De Vries, 2007; Doorman,

2005) to regulate the usage of electricity by the consumers. The consumer would be cut off from

supply the moment it reaches its ‘credit-limit’ in terms of the capacity purchased. The demand-side

aggregators would operate on the micro-market to purchase sufficient electricity for covering their

forecasted requirement.

On the other hand, the supply-side aggregators procure capacity from small generators outside

the load shedding that are willing and able to supply power reliably during this load-shedding

period. It is possible that some small generators from within the region may have excess capacity

that they are willing to offer to the aggregators. The supply side aggregators could also contract this

capacity into their supply portfolio.

As is the case with the demand side aggregators, the supply-side aggregators are free to

decide their tariff structure agreement with the distributed generators. E.g., they may either pay

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them a flat rate per KWh generated or the market price after deducting a commission. The demand

side aggregators bid their contracted capacity in the form of price and volume bids on to the micro-

market.

It is conceivable that large aggregators may prefer to perform both roles thus giving rise to

combined aggregator. However, such a system may lead to oligopolies or monopolies and increase

the risk of market power abuse. In circumstances where such combined aggregators come into

being, strong regulation of the combined aggregators would be required to ensure efficient

functioning of the system.

The presence of an up-to-date policy that protects the interests of all the concerned entities is

necessary for effective functioning of this mechanism. It is important that adequate power is rested

with market regulator for ensuring smooth market functioning of the market and settling disputes. A

credible regulatory entity is necessary to ensure that all market parties adhere to the rules and

regulations. The regulator could be a government body or a private entity depending upon the

nature of the market. The goal of the regulator would be to ensure fair trade, coordination between

market operators and overall administration of the market.

The micro-market is conceptualized as a day-ahead uniform price auction cleared for every

hour of the blackout period. A balancing market could also be created to allow market parties to

adjust their positions closer to dispatch. The market would be operational only during the hours of

the blackout. The supply-side aggregators that clear the market would be obligated to provide the

volume of electricity that clears the market during the specified hour of the day (when load-

shedding occurs in that consumer’s region). Aggregators may be allowed to sign long-term

contracts outside the market for their energy needs. Note that as the objective of this mechanism is

to provide electricity without disrupting the grid, all generation contracts are executed with

distributed generators only and not large generation units.

3. Case-study

In most cases, as the name suggests, back-up generation is installed to provide electricity

during scarcity periods and not as a business investment with any financial returns. In this section,

we analyze the business case for investing in these generation units to exclusively operate on the

micro-market. Therefore in this analysis we ignore the benefits (financial or otherwise) to the owner

of these systems as back-up generation system. We consider two technologies for this analysis

namely, diesel generation and rooftop solar generation. This study is intended to provide an insight

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into the possibility of incentive to invest in distributed generation due to implementation of micro-

markets. Two indicators used to quantify these results are listed below.

• Payback period (PP): It can be defined as number of years required for the system to

recover its initial investment.

• Return on equity (ROE): It is an indicator used to quantify the efficiency of any

investment and can be defined as the annual income as a percentage of the total equity

invested.

To test the robustness of the mechanism in providing incentive for distributed generation,

both indicators are analyzed under varied debt-equity ratios, load shedding hours and revenue

levels. As the study is from an Indian context, we consider risk free rate of return of 8% and an

interest rate of 12% for debt. All results are calculated for a unit size with the ability of producing 1

KWh. The results are permutation of three clearing prices calculated based on different price mark-

up level for the diesel generators (15%, 20% and 25%), three load shedding hour values (6hrs, 8hrs,

10hrs) and six different equity ratios (40% to 90%). We consider a transaction cost of 2% of the

revenue earned by the generator from the market as remuneration for the aggregators and the

market operator.

3.1. Diesel generation

Diesel generation is the most common form of back-up generation encountered in India.

According to CERC data from 2014, 90 GW of diesel generation capacity exists in India (CERC

India, 2015) which is roughly 32% of the total installed capacity in India that is currently estimated

to be 280 GW (Ministry of Power - India, 2015) . These generators would make up a large share of

the total supply that would be traded on the micro-market. It is conceivable that the diesel

generators would also be the marginal units and set the market price. It can be expected that in order

to make profit, the diesel generators may not bid at their marginal price but add a mark up. We

study three different mark-up levels (15%, 20% and 25%). This is based on the assumption that

diesel based generating units would be the marginal plants in the micro-markets.

For calculation of the marginal cost of diesel generation we consider 35% efficiency and the

cost of diesel at 45 ₹/liter (price as of Nov. 23, 2015). Based on these values, the marginal cost for

the diesel-generating unit is calculated to be 14 ₹/KWh. Thus the market price of 17.5 ₹/KWh is

still considerably lower than the value of lost load estimated by CERC. The specifications used in

the following calculations and the capital cost of the diesel generator is calculated based on the

price (INR 150000) of Mahindra 5KVA silent diesel generator set available on e-commerce

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websites (ClickIndia, 2015). The results for the diesel generation unit are tabulated and discussed

below.

Table 1: Payback period (in years) for diesel generators in different scenario settings.

Equity

Ratio

Clearing Price: 16.1 ₹/KWh Clearing Price: 16.8 ₹/KWh Clearing Price: 17.5 ₹/KWh

LS1: 6 hrs. LS: 8 hrs. LS: 10 hrs. LS: 6 hrs. LS: 8 hrs. LS: 10 hrs. LS: 6 hrs. LS: 8 hrs. LS: 10 hrs.

0.4 17 9 7 8 5 4 6 4 3

0.5 11 7 5 6 4 3 4 3 3

0.6 8 5 4 5 3 3 4 3 2

0.7 5 4 3 3 3 2 3 2 2

0.8 3 3 2 2 2 2 2 2 1

0.9 2 2 1 1 1 1 1 1 1

The payback period for a diesel based generation unit under different scenario conditions is

presented in Table 1. As we analyze the investment incentive arising solely from the micro-market,

the revenues considered in these calculations are purely those that are earned by the generator from

the micro-market. It is observed that in 88% of the scenarios the payback period is six years or less,

while in 95% scenarios the payback is within 8 years. In some low revenue scenarios, the payback

period is as high as 17 years. However, in all the scenarios that we considered, the system was able

to payback any debt solely on the income generated from the micro-market.

Table 2: Return on equity for diesel generators in different scenario settings.

Equity

Ratio



0.4 4% 8% 10% 9% 11% 13% 11% 13% 14%

0.5 6% 8% 10% 9% 11% 12% 11% 12% 13%

0.6 6% 8% 9% 9% 10% 11% 10% 12% 13%

0.7 7% 8% 9% 9% 10% 11% 10% 11% 12%

0.8 7% 8% 9% 8% 10% 11% 10% 11% 12%

0.9 7% 8% 9% 8% 10% 10% 9% 11% 12%

1 7% 8% 9% 8% 9% 10% 9% 10% 11%

To understand the ability of this market to provide investment incentive for distributed

generation, we calculated the return on equity for the different scenario settings over a period of 25

years. The results are presented in Table 2. A risk-free rate of return of 8% is considered for

comparing the returns with ‘safe’ investments in government bonds or band deposits. In 74% of the

scenarios, the return on equity is above 8% indicating that investors would gain a greater profit

from investing in a diesel based generator as compared to investing the same equity in risk free

1 LS: Load shedding hours

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investments. In 54% of the scenarios, the return of equity would be 10% or more. The highest

possible return of equity observed was 14% (6% higher than the risk-free rate of return).

3.2. Rooftop PV generation

The government of India is strongly emphasizing and encouraging use of renewable energy

resources for India’s electricity needs (Chandel et al., 2016; Sharma et al., 2012; Shrimali and

Rohra, 2012). Rooftop solar generation is a key renewable technology for distributed generation

(Ghosh et al., 2015; Narula et al., 2012). In this section, we study the possible business case for

distributed solar generation built exclusively to operate in a micro-market. As compared to the case

of diesel generation, we analyze an additional scenario where 100% equity is utilized for

investment.

The data used for calculating cost of modules, subsidies etc., is based on the data used by

Ghosh et al., (2015). To calculate the required capital expenditure, the rooftop photovoltaic module

is sized such that it can supply 1KWh of electricity to the power market when required.

To understand the impact of micro-markets on a rooftop solar system, we first study the

payback period for these systems, assuming they operate exclusively on the micro-market and no

other source of revenue is available. However, we do include the capital subsidy provided for such

systems by the Government of India. The results from for payback period are presented in Table 3.

In 78% scenarios, the payback period is observed to be 6 years or less. This rises to 89% for a

payback period of 8 years or less. Note that the owner of the rooftop PV system is able to payback

debt that may have been acquired for the investment solely from the micro-market revenues.

Table 3: Payback period (in years) for rooftop PV generators in different scenario settings.

Equity

Ratio



0.4 14 8 6 13 8 6 12 7 6

0.5 10 7 5 9 6 5 9 6 4

0.6 7 5 4 7 5 4 6 4 4

0.7 5 4 3 5 3 3 4 3 3

0.8 3 2 2 3 2 2 3 2 2

0.9 2 1 1 2 1 1 2 1 1

The results of ROE over a period of 25 years for different scenarios are presented in Table 4.

It is observed that in 56% scenarios the return is greater than the 8% risk-free rate of return. While,

26% scenarios indicate a return on equity of 10% or greater. Although the PV generators receive

2 LS: Load shedding hours

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higher revenues from the micro-market, the high investment costs lead to lower returns for the

investors. It can also be observed from these results that in 37.5% of the cases with an equity ratio

of 1 (indicating 100% equity participation), the ROE is greater than the risk free rate of return.

Table 4: Return on equity for rooftop PV generators in different scenario settings.

Equity

Ratio



0.4 5% 9% 11% 6% 9% 11% 7% 10% 11%

0.5 6% 9% 10% 7% 9% 10% 7% 9% 11%

0.6 7% 9% 10% 7% 9% 10% 7% 9% 10%

0.7 7% 8% 10% 7% 9% 10% 7% 9% 10%

0.8 7% 8% 9% 7% 9% 10% 7% 9% 10%

0.9 7% 8% 9% 7% 8% 9% 7% 9% 10%

1 7% 8% 9% 7% 8% 9% 7% 8% 9%

These results indicate that the micro-market is able to provide incentive for investment in

distributed generation even as a stand-alone mechanism. There could be a valid business case for

investing in these technologies exclusively for operating on the micro-market. The results also

indicate a higher incentive for diesel generation as compared to solar-rooftop. However, note that

most distributed generation systems are implemented to provide off-grid power to the owners of the

equipment during hours of shortage. Thus, the income from selling the power during idle hours is

additional revenue. Moreover, the results are sensitive to the market clearing prices. Lower prices in

the micro-market may make it less attractive for diesel generator.

3.3. Consumer Benefit

Due to the lack of availability of data, we were unable to quantify the benefit of the micro-

market to the consumer. In our scenarios, the maximum market-clearing price considered is 17.5

₹/KWh. According to literature, the value of lost load (VOLL) for India is estimated to be in the

range of 34 ₹/KWh to 112 ₹/KWh (CERC, 2008). Even assuming the lowest value of VOLL

estimate, it is evident that the there is considerable improvement in consumer welfare due to

avoidance of outages. Thus the micro-market is expected to positively impact consumer benefit.

This high VOLL value would also indicate a high willingness of the consumer to avoid outages,

which could make the micro-market more attractive (due to the possibility of higher clearing

prices). Further data collection and analysis is required for quantifying these findings.

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4. Barriers

The barriers to implementation of such mechanisms can be broadly grouped into two

categories policy barriers and technological barriers.

In context of technological barriers for implementing the proposed mechanisms, in this study

we consider the existence of a grid network as a prerequisite. However in many areas the

distribution grid infrastructure is not adequately robust to handle the two-way flows that would

occur. As discussed in literature, much investment is required to update the current distribution

infrastructure in India. Another issue is the ability (and cost) of the system operator to maintain

sufficient voltage levels in the distribution networks for the regions buying electricity from the

micro-market. An important requirement for the smooth functioning of this system is the

installation of smart meters. A smart metering system would be required to regulate the

consumption on the consumer side and to measure generation on the supply end. The installation of

such meters entails a high cost. If the aggregators were required to invest in providing this

infrastructure, the transaction cost may be too high for such a venture to be attractive for them.

In this study, we consider a transaction cost of 2% of the revenue earned by the generator

from the market to remunerate the aggregators and the market operator. It is important to calculate

the actual cost of running such a mechanism for the aggregators and the market operator. As this

would be a purely profit based venture for the aggregator, realistic cost estimates would be key in

establishing attractiveness of investing in such a venture.

5. Conclusions

In this research we propose a micro-market for providing electricity during load shedding.

Micro-markets would make investments in diesel and solar energy based distributed generation

attractive, even if these distributed generation systems depend exclusively on these micro-market

for revenues. For both distributed generation systems analyzed in this research, in many of the

scenarios, the return on equity is higher than the risk free rate of return even at a market clearing

price significantly lower than the estimated value of lost load. Considering the conservative market

clearing prices and VOLL values from literature, a higher willingness to pay on the consumer side

could be expected, which would make the micro-market more attractive for generators.

We can also conclude that consumers would strongly benefit from the avoidance of outages.

A policy instrument such as the micro-markets for electricity can lead to improvement in electricity

adequacy for industrial as well as residential sectors. It could lead to an improvement in the overall

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of productivity in industries that depend on electricity and would thus reflect positively on the

macro-economic indicators of the country, especially if this system is implemented in multiple

regions.

The system presented here is easy to replicate across the entire country and could evolve into

a more integrated system in the future. Furthermore such a system could be implemented in many

other developing nations.

The authors acknowledge that this research is very much a work in progress. Development of

a detail model of such a system with more accurate assumption is required for further in-depth

analyses and development of this research in the future.

Acknowledgments

The authors would like to thank all the experts who took part in this survey for their time and

valuable insights. Pradyumna Bhagwat has been awarded an Erasmus Mundus Joint Doctorate

Fellowship. The authors would like to express their gratitude towards all partner institutions within

the program as well as the European Commission for their support.

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