Design of load balancing mechanism for Indian electricity markets

Safiullah, Hameed; Hug, Gabriela; Tongia, Rahul

doi:10.1007/s12667-016-0199-3

Cited by 17 publications

(14 citation statements)

References 37 publications

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“…The same value is 100 kg/MWh for the 16 higher emission states. Moreover, in these higher emission states, median time-of-day marginal hydro generation is higher during the dry season (2–14%) than the monsoon season (3–9%), consistent with Indian dispatch practices that use hydro as marginal generators during dryer months…”

Section: Resultsmentioning

confidence: 99%

“…We calculate MEFs for each state using two methods: linear regression − ,, and differentiation of emissions-generation curves . We do not estimate MEFs by identifying the emission factor of the marginal generator (i.e., the last, costliest generator in the merit order) because (1) more than one generator or combinations of generators may change output to meet demand and (2) grid operators in India use hydrogenerators as marginal generators based on nonmerit order heuristics, and (3) we have access to only generation and transmission output in the 2030–2031 modeling results, not the merit order input. However, as sensitivity, we present emission factors from the marginal generator in 2017–2018 in Figures S26–S35.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…Individual states are balancing areas that contract with and schedule power (“self-scheduling”) from various portfolios of plants owned by the central government, by state governments, and by the private sector. These long-term power purchase agreements cover 90% of wholesale power volumes in India . With some regional and national coordination, states use a combination of economic dispatch and historical practices (heuristics) to choose which plants to procure power from to deliver to consumers , Moreover, the central government and state governments have overlapping jurisdiction over the power sector.…”

Section: Introductionmentioning

confidence: 99%

“…These long-term power purchase agreements cover 90% of wholesale power volumes in India . With some regional and national coordination, states use a combination of economic dispatch and historical practices (heuristics) to choose which plants to procure power from to deliver to consumers , Moreover, the central government and state governments have overlapping jurisdiction over the power sector. Thus, not only do fuel mixes and emissions of electricity consumed vary by state, but so do policies governing emissions from the power sector. , Lastly, on average, about 20% of electricity generated is lost due to technical and nontechnical losses in transmission and distribution (T&D losses), with values ranging between 9 and 47% in different states. , To meet a certain level of electricity demand power plants must generate additional electricity, resulting in more emissions.…”

Section: Introductionmentioning

confidence: 99%

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Current and Future Estimates of Marginal Emission Factors for Indian Power Generation

Sengupta¹,

Spencer

Rodrigues

et al. 2022

Environ. Sci. Technol.

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Emission factors from Indian electricity remain poorly characterized, despite known spatial and temporal variability. Limited publicly available emissions and generation data at sufficient detail make it difficult to understand the consequences of emissions to climate change and air pollution, potentially missing cost-effective policy designs for the world’s third largest power grid. We use reduced-form and full-form power dispatch models to quantify current (2017–2018) and future (2030–2031) marginal CO2, SO2, NOX, and PM2.5 emission factors from Indian power generation. These marginal emissions represent emissions changes due to small changes in demand. For 2017–2018, spatial variability in marginal CO2 emission factors range 3 orders of magnitude across India’s states. There is limited seasonal and intraday variability with coal generation likely to meet changes in demand more than half the time in more than half of the states. Assuming the Government of India approximate 2030 targets, the median marginal CO2 emission factor across states decreases by approximately a factor of 2, but emission factors still span 3 orders of magnitude across states. Under 2030–2031 assumptions there is greater seasonal and intraday variability by up to factors of two and four, respectively. Estimates provide emission factors to evaluate interventions such as electric vehicles, increased air conditioning, and energy efficiency.

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Section: Resultsmentioning

confidence: 99%

Section: Materials and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Current and Future Estimates of Marginal Emission Factors for Indian Power Generation

Sengupta¹,

Spencer

Rodrigues

et al. 2022

Environ. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Reliable power grid service depends primarily on the right balance between supply and load. It is not easy to maintain the balance between the consumer and the utility side [8]. It becomes much more challenging with the increase of distributed energy generation.…”

Section: Review On Dsmmentioning

confidence: 99%

Various demand side management techniques and its role in smart grid–the state of art

Muthuselvi

Balasubramanian²

2022

IJECE

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The current lifestyle of humanity relies heavily on energy consumption, thus rendering it an inevitable need. An ever-increasing demand for energy has resulted from the increasing population. Most of this demand is met by the traditional sources that continuously deplete and raise significant environmental issues. The existing power structure of developing nations is aging, unstable, and unfeasible, further prolonging the problem. The existing electricity grid is unstable, vulnerable to blackouts and disruption, has high transmission losses, low quality of power, insufficient electricity supply, and discourages distributed energy sources from being incorporated. Mitigating these problems requires a complete redesign of the system of power distribution. The modernization of the electric grid, i.e., the smart grid, is an emerging combination of different technologies designed to bring about the electrical power grid that is changing dramatically. Demand side management (DSM) allow customers to be more involved in contributors to the power systems to achieve system goals by scheduling their shiftable load. Effective DSM systems require the participation of customers in the system that can be done in a fair system. This paper focuses primarily on techniques of DSM and demand responses (DR), including scheduling approaches and strategies for optimal savings.

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Electrical Energy Storage Influencing Shift in Grid Balancing Approach

Nazar

Anwer

2021

Lecture Notes in Electrical Engineering

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Design of load balancing mechanism for Indian electricity markets

Cited by 17 publications

References 37 publications

Current and Future Estimates of Marginal Emission Factors for Indian Power Generation

Current and Future Estimates of Marginal Emission Factors for Indian Power Generation

Various demand side management techniques and its role in smart grid–the state of art

Electrical Energy Storage Influencing Shift in Grid Balancing Approach

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