Parul Mathuria

GenCo's Integrated Trading Decision Making to Manage Multimarket Uncertainties

Fossil fuel generation companies (GenCos) trade in multiple uncertain energy markets: fuel and carbon markets on upstream side while electricity market on downstream side. Global economic and environmental benefits lead these markets to pursue overlapping goals, making them highly interactive. GenCos may identify optimal trading strategies for upstream and downstream trading in an integrated framework, to manage an overall secure and profitable position. Further, severe unpredictability of energy market prices may necessitate a GenCo to make trading plans which perform better meeting its goals. Under severe uncertainty of involved markets, this paper proposes Information Gap Decision Theory (IGDT) based approach to select three interrelated trading portfolios, in an integrated framework. Results from a realistic case study provide a comprehensive decision insight to address risk-averse and risk-seeking behavior of GenCo, explicitly highlighting importance of co-variation in prices of interactive markets.

Risk constrained short term electricity procurement for open access consumer in India

Open access is a major power sector reform in energy deficit India, and encourages short term trading for meeting variations in demand. An open access large consumer in India, can participate in short term trading through bilateral contracts, power exchanges (PXs) or unscheduled interchange (UI) transactions. In addition, it needs to satisfy obligations of renewable purchase. Prices of PXs day ahead market are uncertain, while UI charges for frequency variations vary widely due to real time deviations in withdrawals. Considering these uncertainties in the backdrop of Indian power sector, this work proposes an optimal short term power procurement strategy for large consumer, from available trading options. A small self generation facility and demand flexibility is also considered. A practical case study of Indian open access consumer is considered to show the effectiveness of proposed approach.

Robust self scheduling framework for GenCos with portfolio optimization

This work presents a self scheduling problem of a thermal GenCo, trading electricity in a daily spot and subsequent adjustment market, to secure maximum feasible profit under the uncertainties of both the markets. The work proposes an Information Gap Decision Theory (IGDT) based framework that enables GenCo to make robust decisions for self-scheduling as well as trading portfolio selection in daily electricity markets. A realistic case study of PJM market is considered which provides a range of decisions about both unit commitment and allocation in both the markets for a rational GenCo, based on the trade-off existing between robustness and targeted profit.

Impact of short term electricity procurement of an open access consumer on Indian grid

Unscheduled Interchange (UI) mechanism has emerged as a powerful tool for maintaining grid discipline, penalizing the market players, causing deviations in the system. A buyer pays UI penalty for over-withdrawal of power more than the scheduled one based on the grid condition. Such buyers having demand fluctuations may end up paying UI penalty at the real time. This paper proposes a planning model for a large open access consumer in India, purchasing from bilateral contracts and multiple Day Ahead Markets (DAMs). The proposed model can shift consumers expected demand by accounting the UI deviations to minimize procurement cost. A small self generation unit and renewable purchase obligations are also considered. This work considers price uncertainty of both markets. The overall problem of cost and risk minimization is handled by mean variance approach. Results indicate that the consumer can plan demand scheduling for the planning period as well as can help in improving grid frequency at the real time.

Uncertainty and risk management in electricity market: Challenges and opportunities

During last two decades, power industry underwent major changes all over the world. One is regulatory reform towards distributed and competitive structure, in which market forces drive the electricity prices, and the other is a large share of renewable in total electricity generation mix. These bring in unpredictable future conditions i e. uncertainty in prices and volume of electricity at the time of planning. These significantly changed the traditional working of various entities in the power sector and raised many challenges and opportunities. This paper briefs some of the challenges and opportunities to major entities (generation companies, retailers, large consumer and system operators) of restructured power sector and highlights the necessity of uncertainty consideration and its various impacts from the perspective of different entities.

Large consumer's purchase portfolio optimization in electricity market

Large consumers are increasingly involved in direct purchase from wholesale electricity markets, consisting of different markets and contractual instruments. Prices of these trading options are highly uncertain. Each trading options has its own unique price-risk characteristic. Consumers may allocate their purchase among available trading options, to achieve minimum purchase cost while also minimizing risk. This work proposes a purchase portfolio optimization approach for large consumers electricity procurement from spot market, multi-area bilateral contracts and self-generation, considering price uncertainties of pool and congestion charges, using Markowitz mean variance portfolio theory. Analysis based on a practical case of PJM market illustrates that due to interdependent behavior of multiple uncertain trading options, diversification potential of the portfolio is improved with multi-area trading. Results highlight that correlations between trading options strongly impact purchase allocation.

GenCo's integrated trading decision making to manage multimarket uncertainties

Fossil fuel generation companies (GenCos) trade in multiple uncertain energy markets: fuel and carbon markets on upstream side while electricity market on downstream side. Global economic and environmental benefits lead these markets to pursue overlapping goals, making them highly interactive. GenCos may identify optimal trading strategies for upstream and downstream trading in an integrated framework, to manage an overall secure and profitable position. Further, severe unpredictability of energy market prices may necessitate a GenCo to make trading plans which perform better meeting its goals. Under severe uncertainty of involved markets, this paper proposes Information Gap Decision Theory (IGDT) based approach to select three interrelated trading portfolios, in an integrated framework. Results from a realistic case study provide a comprehensive decision insight to address risk-averse and risk-seeking behavior of GenCo, explicitly highlighting importance of co-variation in prices of interactive markets.

Info-gap approach to manage GenCo's trading portfolio with uncertain market returns

An independent generation company (GenCo) secures its future trading position by managing its portfolio among multiple trading options. Future returns of these trading options are not known during decision making and are traditionally estimated using probabilistic or fuzzy methods. Quantifying such uncertainty of market returns by conventional methods does not reflect the information gap existing between estimated and actual market returns. Based on quantification of this information gap, the paper proposes GenCos portfolio optimization using a non-probabilistic Information Gap Decision Theory (IGDT). This framework comprehensively models GenCos behavior in deciding its trading strategy. Considering GenCos risk-averse behavior, the framework provides decisions that are robust towards losses, while considering its risk-seeking behavior the framework offers opportunity to capture windfall gains. The proposed approach has been validated through practical case study of PJM market.

IGDT based Genco's trading decision making in multimarket environment

Fossil fuel gencos are subject to influence of multiple uncertain but interactive energy and emission markets. It procures production resources from fuel and emission market and sells its generation through multiple contracts in electricity market. With increasing volatility and unpredictability in energy markets, a genco needs to make prudent decision to manage its trading in all involved markets, to guarantee minimum profit. Considering the existing market uncertainties and associated information gap, this paper proposes a robust decision making approach for gencos trading portfolio selection in all three involved markets, based on Information Gap Decision Theory (IGDT). Results from a realistic case study provides a range of decisions for a risk averse genco, appropriate to its nature, and based on the trade-off existing between robustness and targeted profit.

Carbon price risk influence on GenCo's portfolio optimization

Worldwide stress on low carbon economy and reducing aggregate CO2 emission levels exposed fossil fuel GenCos to carbon risk associated with prices of carbon permits needed to be environmentally compliant. This risk is substantial for fossil fuel GenCos aiming to maximize profit. This paper addresses a power portfolio optimization approach for a fossil fuel GenCo to maximize profit and minimize risk of volatile input costs and output revenue. Carbon price risk along with fuel and electricity price risk with correlation between all revenue and cost side markets has been considered for portfolio selection using Markowitz mean variance theory. A realistic case study on Nordpool market illustrate that carbon price uncertainty considerations alter trading decision of GenCo in electricity market for efficient risk management. Correlated revenue and cost side markets provides better tradeoff in terms of profit and risk for same risk averse level for GenCo. Under strong correlation of electricity and carbon market a higher allocation in spot market provides risk protection. The carbon price risk impact is prominent for high emission GenCos.