Elsevier

Energy

Volume 93, Part 1, 15 December 2015, Pages 963-975
Energy

A study of feasible smart tariff alternatives for smart grid integrated solar panels in India

https://doi.org/10.1016/j.energy.2015.09.100Get rights and content

Highlights

  • Study of net metering data in smart grid pilot project in India.

  • Scenario analysis for savings in electricity under different cases.

  • Comparison of net metering and gross metering mechanisms.

  • Net metering is found to be more beneficial than gross metering.

  • Suggestions for alternative net metering techniques for developing countries.

Abstract

With the advent of grid connected solar panels in India, the requirement of a separate mechanism for metering and billing is foreseen. The policy framework for addressing this need is under process in various states of India. In the smart grid pilot project at Puducherry, India, a simple net metering mechanism has been incorporated to evaluate and understand the performance of green energy generation through solar panels. The present paper draws a comparison between net metering and gross metering mechanisms, through the analysis of net meter data collected for three different types of consumers from the pilot project at Puducherry. Different scenarios have been evaluated to infer the impacts of specialized billing mechanisms as well as the payback periods on investment made for solar energy systems and the savings that is reflected in the monthly bills. Feed in tariff renders full credit to the renewable energy customers on their electricity bills for the amount of green power, which is sent back to the main grid. This simple mechanism of a credit system would prove to be the most important energy policy for a nation to encourage sustainable energy generation. Due to wide variations in tariffs, requirements and efficiency of utilities across the different states in India, a policy which can accommodate mechanisms of community net metering and aggregate net metering had become a necessity. The paper signifies the crucial and immediate necessity for a feasible and acceptable energy policy so as to realize the benefits of power from the sun.

Introduction

The growth rate of energy usage for the developed countries is about 1% per year whereas it can be up to 5% for the developing nations [1]. The unprecedented growth rate requires a continuous supply of energy to meet the needs of a growing economy. There are various options to meet the demand requirements of energy, like implementing programs and standards for efficient use of energy, increasing the generation of electricity through fossil fuels or by utilizing distributed energy resources and energy storage strategies [2], [3], [4], [5], [6]. Increased awareness regarding the benefits of renewable resources and its implied financial benefits in the long run has made people to use it as an alternative for generation of electricity. The policy framework is in the development stage and is being revised from time to time in many developed countries [7] and various mechanisms to incentivize green power are being formulated. Net metering and gross metering are widely used for compensating green power generated by consumers. Various types of mechanisms like PPA (pre-purchase agreement), green pricing, REC (renewable energy credits) etc. are being implemented and revised by utilities for checking the feasibility of the mechanism and realizing the benefits of the renewable energy resources.

In developing countries, where there is high deficit of energy, renewable energy sources can prove to be a significant alternative, which in the long term would give sustainable energy to the people. With the advent of smart grid, export of units generated by a consumer is now made possible. This gives a whole new dimension to generation and usage of electricity by the same person coining a new term prosumer. As the nations are moving towards smart cities, the integration of renewable energy in the smart grid would lead towards a more sustainable economy. Jagruti et al. [8] studied the implementation of smart grid pilot project at Puducherry, India which offers a platform to test various metering features of the installed smart meters. This would in turn require policies and mechanisms to compensate for the energy generated by the user.

Section snippets

Renewable energy markets for developing countries

The renewable energy markets of the developing countries vary as compared to the developed countries. The increase in investment in renewable energy market in developing nations was 36% as compared to a modest rise of 3% for developed nations in 2014 [9]. This led to an increase of 6% in global share of renewable energy of developing countries. The investment in renewable energy market in India rose by 25% during the period 2004–11 [9].

Developing countries like China, Brazil and India showed

Feed in tariffs

FIT (Feed in tariff) refers to a differential pricing scheme applied to the energy generated by the consumers from renewable energy sources like solar, wind and biomass, which is fed back to the grid.

Feed in tariffs requires licenses, which permits consumers to become prosumers (consumer + producer). FITs are paid for each unit of electricity generated that is rupees per kWh. The feed in tariffs depend on various factors like the type of technology installed (tariff differentiation), the date

Data

The data is collected from three net meters, which are first of its kind installed in India. These net meters are able to record both imported and exported units of electricity in different registers provided in the smart meter for recording data, from the grid and back to the grid respectively. The meters also record net unit of electricity in a separate register, which is the difference of electricity imported from the grid and the amount of surplus electricity exported back to the grid. The

The architecture

Fig. 3 shows the architecture employed for net metering at the site. The advanced metering infrastructure designed to import and export electricity and to communicate information bi-directionally is connected to a DCU i.e. data concentrator unit. The data concentrator unit is a core component of the data acquisition system of the smart grid control center. It is essential for the data and energy management in AMI. The data concentrator unit accumulates data from a specified number of smart

Analysis of the data

The software used to generate surface maps (Fig. 4, Fig. 5, Fig. 6) is Matlab 2013 and rest of the maps and charts have been generated using SAP Lumira.

The surface map in Fig. 4 shows net kWh (import–export) of energy used by consumer 1. In the map, net energy can be negative, when generation of solar energy is greater than consumed energy, hence the scale of net kWh starts with negative values. The energy usage remains close to negative values of net energy consumption for most of the duration

Scenario analysis

The scenario analysis is carried out to analyze the financial savings made through renewable energy sources. Three scenarios; net metering, gross metering and conventional metering (without solar energy) is discussed below.

The rates for residential as well as commercial settlements are used for calculation in the analysis. The residential as well as commercial electricity rates are flat rates that are non-time-differentiated rates. There is a limit of 150 kWh of consumption for electricity per

Conclusion

The advancement in renewable energy technology as well as its success in imparting sustainable electrical energy has paved the way for large scale generation of electricity through renewable energy resources. The analysis of data provides insights into variations in the export of generated green power and uncertainty in usage pattern. The distinct behavior of the consumers demands digging deep in to the data analytics before designing a strong framework for feed in tariffs in India. The

Acknowledgments

This data used in this paper is based on smart grid pilot project, Puducherry of Power Grid Corporation of India Ltd. Any opinion, finding, conclusion or recommendations expressed in the paper are those of authors and do not necessarily reflect those of PGCIL.

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