Deb Chattopadhyay

Game-Theoretic Frameworks for Demand Response in Electricity Markets

This paper presents game-theoretic frameworks for demand response at both electricity market and consumer levels. First, the interaction between a demand response aggregator (DRA) and electricity generators is modeled as a Stackelberg game in which the DRA, as the leader of the game, makes demand reduction bids, and generators, as followers, compete for maximizing their profits based on the reduced demand. Next, the interaction between the DRA and consumers is modeled as a mechanism design problem wherein the DRA seeks to minimize the aggregate inconvenience of consumers while achieving the targeted load curtailment. The inconvenience function of each consumer is captured by a type value, which is used by the DRA to solve the load curtailment problem. A Vickrey-Clarke-Groves-based mechanism is proposed, which guarantees that each consumer reveals its true type value to the DRA. A case study of the Stackelberg game shows that, in the South Australian electricity market where there is significant renewable penetration, peak period demand response provides the maximum potential profit, but off-peak demand response even in a concentrated market is not financially attractive.

Modeling Greenhouse Gas Reduction From the Australian Electricity Sector

The Australian electricity sector is expected to undergo major changes to reduce the current sectoral CO2 emission of 190 million tons to 96 million tons by 2050. This paper summarizes two major modeling studies that have been undertaken since 2006 to understand the full set of investment, price and financial impact on existing generators, especially coal-based generators. We have used a long-term capacity and dispatch optimization model to comprehensively analyze both least-cost and market-led expansion of the system to accommodate alternative emission reduction targets from a shallow cut to a deep cut. The modeling results demonstrate the cost of meeting the target can be over

Allocation of unit start-up costs using Cooperative game theory

30 billion in NPV terms. A mix of clean coal technologies, gas and nuclear technologies is expected to displace the existing stock of conventional coal which varies significantly depending on the emission reduction target. The analysis also show that mandatory renewable targets or technology standards are inefficient policies in comparison to a market-based policy such as the proposed emissions trading scheme.

A Game-Theoretic Analysis of Wind Generation Variability on Electricity Markets

This paper discusses a three-part generation offer strategy that enables generators to put in unbundled variable operating costs and fixed start-up/no-load costs. We then propose methods based on cost sharing axioms to allocate fixed start-up/no-load costs among electricity consumers/load/retailers that take into account equity and rationality considerations. We focus on the single period cost allocation first. We apply three well-known game theoretic axioms: the core, the nucleolus, and the Shapley value. We discuss the relative merits and demerits of each criterion and also explore certain theoretical conditions for the existence of the core and the Shapley value lying inside the core. Finally, the multiperiod start-up cost allocation problem is studied. Allocations based on individual periods vis-a/spl grave/-vis composite allocation for all periods are compared and contrasted. Numerical examples are used to illustrate all theoretical concepts.

Capacity and Energy-Only Markets Under High Renewable Penetration

Wind generation variability in an energy-only market such Australian National Electricity Market (NEM) can create significant revenue uncertainties for incumbent generators and substantially increase price risks faced by retailers. This paper presents a Cournot game model to formally analyze how high volatility of wind generation in a concentrated energy-only market can raise the peak/shoulder period (of typically low wind generation) prices to offset the foregone revenue during off-peak periods (of high wind generation). A Monte Carlo simulation around a Cournot game is formulated as an inter-temporal nonlinear optimization problem to assess these issues. The model is implemented for the South Australian zone of the Australian NEM that has experienced high growth in wind generation in recent years. The model results support some of the observed spot pricing behavior in the region in recent years. These findings have significant ramifications for the efficacy of the energy-only market in scenarios with high penetration of intermittent generation.

A game-theoretic analysis of demand response in electricity markets

This paper presents a multi-nodal intertemporal Cournot gaming model with transmission constraints and uses it to simulate energy-only and capacity-energy market designs in the presence of uncertainties stemming from intermittent renewable power generation. Both market paradigms are compared to a competitive benchmark in order to determine which one performs better in a concentrated market with significant penetration of wind and solar generation. As a specific example, the model is applied to the South Australian zone of the Australian National Electricity Market (NEM). The simulation results for the time interval 2013-2030 show that the capacity-energy market has the potential to induce significant new capacity and push prices much closer to the competitive level in contrast to the current energy-only market design.

Cross-border power trading in South Asia: Modelling analysis to assess economic benefits

This paper presents a game-theoretic approach to demand response in electricity markets. A Stackelberg game model is developed to capture the interplay between a Demand Response Aggregator (DRA) and electricity generators, where the DRA acts the leader of the game and makes demand reduction bids by taking into account their profitability. The classical generators respond by adjusting their electricity generation levels which leads to an equilibrium solution of the resulting strategic (non-cooperative) game in the competitive wholesale electricity market. A numerical analysis of the Stackelberg game shows that highly concentrated markets during the peak hours are the most profitable scenarios for the demand response from the DRAs perspective.

Electrification of remote villages in Assam (India): Issues and case studies

There has been an unprecedented growth in electricity demand in South Asian countries in the last decade - most notably in India. There are significant economic and reliability benefits of power trading on a regional basis among the South Asian countries that largely remain unexploited to date. For instance, large scale power trading between India and Nepal/Bhutan can unleash massive hydro potential in excess of 100 GW that could be the key to reducing fuel costs, unserved energy and CO2 emissions throughout South Asia. This study is one of the first attempts to put in context how significant these benefits can be even in the short term. We have undertaken a modeling study that includes load flow analysis, transmission constrained investment and dispatch optimization and Monte Carlo simulation of unserved energy, to assess these benefits. We have estimated annual benefits for the year 2016/17 which shows economic and reliability benefits for a single year may justify the entire investment needed in the interconnection infrastructure. If we consider the significant environmental benefits in terms of CO2 reduction, total benefits would further outweigh the costs.

Analysis of upstream gas network constraints for power generation in Queensland

Rural electrification in India has received considerable attention and funding lately. However, these efforts are often disorganized, and do not consider the full set of locally available resources. This study presents our analysis for Assam, a Northeastern state in India, which has more than 2000 (or, 25%) of un-electrified villages. Our site visits, discussions, research and analysis spanning over a year, show that it is possible to efficiently combine local resources and distribution network extension using SWER, to electrify many of these villages at a fraction of a cost of the current policy measures using solar home lighting systems. We also emphasise the need to customize the solution for different areas given the variation in local resources among other things. The sample projects we have selected are currently being considered for pilot projects, to be rolled out throughout the state and possibly other states.

Modelling renewable energy impact on the electricity market in India

The degree of structural and operational integration between gas and electricity markets has increased sharply in the last decade internationally and also in Australia. This paper investigates the optimal gas production profile for the state of Queensland (QLD) in Australia, with a view to analyzing the ramifications of gas network constraints for large-scale gas-fired power generation (GPG). GPG is projected to grow significantly as part of the Australian governments strategy to reduce carbon emissions and wind down coal-based generation. This paper employs a least-cost optimization using a linear programming (LP) model to understand the level of expansion that pipeline infrastructure would need to cope with forecast power generation demand. Results show the QLD gas network will reach capacity limits by 2015 at significant cost to the economy, demonstrating a need for further investment. There are significant network constraints that would render meeting demand from the power sector a major challenge.