Efficiency and Market Power in Electricity Markets with Inelastic Demand, Energy Storage, and Hybrid Energy Resources

This thesis studies electricity markets and analyzes market mechanisms - operation rules for participants in achieving supply-demand balance, to understand how competition between resources, e.g., conventional generators, inelastic loads, and new market participants, such as energy storage and hybrid resources, affects market efficiency. We first consider the participation of conventional resources in a two-stage market, i.e., day-ahead and real-time settlement. Although designed to allocate resources efficiently and prevent speculation, price manipulation by strategic participants can undermine these goals. To address price manipulation, some markets have proposed system-level market power mitigation (MPM) policies, which substitute noncompetitive bids with default bids based on estimated generation costs. Using equilibrium analysis, we illustrate that such a policy in the day-ahead stage is more robust to price manipulations than in real-time, which may lead to non-equilibrium solutions. Despite being inelastic, loads can shift their allocation between the two stages to manipulate prices and reduce their payments. Further, heterogeneity in cost coefficients, estimation of dispatch cost in excess, and demand uncertainty tend to benefit generators. Together, system-level MPM policies can have unintended consequences when implemented without accounting for the conflicting interests of participants. We then study how integrating energy storage affects market efficiency. Our analysis indicates that the existing participation mechanism, where energy storage bids power in a market, may diminish market benefits due to its unique operational characteristics, e.g., the operating cost depends on charge-discharge cycles, unlike conventional generators. We propose a novel market mechanism based on an energy-cycling function that maps cycle depth to per-cycle prices. An equilibrium analysis illustrates the efficient competitive equilibrium that aligns with the social planner problem, i.e., net surplus maximization. However, at the Nash equilibrium, storage incurs reductions in profit relative to the competitive equilibrium due to price manipulation by strategic generators. Finally, we study the participation of hybrid resources combining energy storage and renewable energy sources. We use the New York zonal model as an example of a large-scale electricity market to benchmark the performance of the following two types of market models. We consider (i) a granular model, where the market operator manages the operation of constituent energy storage, and (ii) an integrated model, where the owner manages the storage operation. Our analysis shows that granular models lead to lower operating costs but add computational complexity, which may not be desirable from the operator's perspective. Though less computationally intensive, integrated models result in more intervals violating the physical limits of constituent energy storage

Market Power Mitigation in Two-stage Electricity Market with Supply Function and Quantity Bidding

The main goal of a sequential two-stage electricity market -- e.g., day-ahead and real-time markets -- is to operate efficiently. However, the price difference across stages due to inadequate competition and unforeseen circumstances leads to undesirable price manipulation. To mitigate this, some Independent System Operators (ISOs) proposed system-level market power mitigation (MPM) policies in addition to existing local policies. These policies aim to substitute noncompetitive bids with a default bid based on estimated generator costs. However, these policies may lead to unintended consequences when implemented without accounting for the conflicting interest of participants. In this paper, we model the competition between generators (bidding supply functions) and loads (bidding quantity) in a two-stage market with a stage-wise MPM policy. An equilibrium analysis shows that a real-time MPM policy leads to equilibrium loss, meaning no stable market outcome (Nash equilibrium) exists. A day-ahead MPM policy, besides, leads to a Stackelberg-Nash game with loads acting as leaders and generators as followers. In this setting, loads become winners, i.e., their aggregate payment is always less than competitive payments. Moreover, comparison with standard market equilibrium highlights that markets are better off without such policies. Finally, numerical studies highlight the impact of heterogeneity and load size on market equilibrium

Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Background To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states. Methods We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 × 5 km grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states. Findings The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2–17.8) to 62.8% (95% UI 61.5–64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1–6.1) to 30.0% (95% UI 28.2–31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5–11.9) to 51.0% (95% UI 49.9–52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3–42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3–46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8–55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys. Interpretation CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets. Keywords Child growth failureDistrict-levelGeospatial mappingInequalityNational Nutrition MissionPrevalenceStuntingTime trendsUnder-fiveUndernutritionUnderweightWastingWHO/UNICEF target

Integration of Hybrids into Wholesale Power Markets

With growing commercial activity around utility-scale hybrid storage projects in the Unites States, independent system operators (ISOs) and regional transmission organizations (RTOs) are faced with making decisions on how to represent such emerging technology resources in the market clearing software through the definition of hybrid resource participation models. System operators are facing increasing uncertainties around efficient and reliable ways to operate these resources given the ambiguity around their impacts, particularly when high levels of hybrid resources are present. This study aimed to evaluate and compare the performance implications of different hybrid resource participation models in a realistic wholesale electricity market setting with significant deployment of hybrid resources, and to provide the industry with metrics that quantify the advantages and disadvantages of different participation options using realistic electricity market simulations. The different participation models are compared in terms of the impact to reliability of the overall system, the ability of the market to access the full capabilities of hybrid resources as measured by the economic efficiency, and asset profitability

SARS-CoV-2 seroprevalence among the general population and healthcare workers in India, December 2020–January 2021

Background: Earlier serosurveys in India revealed seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) of 0.73% in May–June 2020 and 7.1% in August–September 2020. A third serosurvey was conducted between December 2020 and January 2021 to estimate the seroprevalence of SARS-CoV-2 infection among the general population and healthcare workers (HCWs) in India. Methods: The third serosurvey was conducted in the same 70 districts as the first and second serosurveys. For each district, at least 400 individuals aged ≥10 years from the general population and 100 HCWs from subdistrict-level health facilities were enrolled. Serum samples from the general population were tested for the presence of immunoglobulin G (IgG) antibodies against the nucleocapsid (N) and spike (S1-RBD) proteins of SARS-CoV-2, whereas serum samples from HCWs were tested for anti-S1-RBD. Weighted seroprevalence adjusted for assay characteristics was estimated. Results: Of the 28,598 serum samples from the general population, 4585 (16%) had IgG antibodies against the N protein, 6647 (23.2%) had IgG antibodies against the S1-RBD protein, and 7436 (26%) had IgG antibodies against either the N protein or the S1-RBD protein. Weighted and assay-characteristic-adjusted seroprevalence against either of the antibodies was 24.1% [95% confidence interval (CI) 23.0–25.3%]. Among 7385 HCWs, the seroprevalence of anti-S1-RBD IgG antibodies was 25.6% (95% CI 23.5–27.8%). Conclusions: Nearly one in four individuals aged ≥10 years from the general population as well as HCWs in India had been exposed to SARS-CoV-2 by December 2020