Related papers: Volatility of Power Grids under Real-Time Pricing
This paper studies the problem of frequency regulation in power grids, while maximizing the social welfare. Two price-based controllers are proposed; the first one an internal-model-based controller and the second one based on a continuous…
In the information-based approach to asset pricing the market filtration is modelled explicitly as a superposition of signals concerning relevant market factors and independent noise. The rate at which the signal is revealed to the market…
As an essential measure to combat global warming, electric vehicles (EVs) have witnessed rapid growth. Flexible EVs can enhance power systems' ability to handle renewable generation uncertainties. How EV flexibility can be utilized in power…
We consider "time-of-use" pricing as a technique for matching supply and demand of temporal resources with the goal of maximizing social welfare. Relevant examples include energy, computing resources on a cloud computing platform, and…
This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are…
Electricity markets are experiencing a rapid increase in energy storage unit participation. Unlike conventional generation resources, quantifying the competitive operation and identifying if a storage unit is exercising market power is…
Many loads have flexibility in demand that can be used to provide ancillary services to power grids. A large body of literature exists on designing algorithms to coordinate actions of many loads to provide such a service. The topic of…
We develop a new identification strategy for demand estimation when cost shifters may not be available and there are substantial variations in demand over time. This approaches relies on a kind of nonlinear difference-in-differences, in…
Electricity markets differ in their ability to meet power imbalances in short notice in a controlled fashion. Relatively flexible markets have the ability to ramp up (or down) power flows across interties without compromising their ability…
The increasing penetration of volatile renewables combined with increasing demands poses a challenge to modern power grids. Furthermore, distributed energy resources and flexible devices (electric vehicles, PV generation, ...) are becoming…
It is well known that highly volatile control laws, while theoretically optimal for certain systems, are undesirable from an engineering perspective, being generally deleterious to the controlled system. In this article we are concerned…
During the last years, European intraday power markets have gained importance for balancing forecast errors due to the rising volumes of intermittent renewable generation. However, compared to day-ahead markets, the drivers for the intraday…
The reliability of the electric grid has in recent years become a larger concern for regulators, planners, and consumers due to several high-impact outage events, as well as the potential for even more impactful events in the future. These…
Demand response (DR) refers to change in electricity consumption pattern of customers during on-peak hours in lieu of financial gains to reduce stress on distribution systems. Existing dynamic price models have not provided adequate success…
Demand flexibility can offset some of the variability introduced on the supply-side by variable renewable generation. However, most efforts (e.g. control of residential vehicle charging) focus on short durations -- typically on the scale of…
With the proliferation of advanced metering infrastructure (AMI), more real-time data is available to electric utilities and consumers. Such high volumes of data facilitate innovative electricity rate structures beyond flat-rate and…
In a stochastic volatility framework, we find a general pricing equation for the class of payoffs depending on the terminal value of a market asset and its final quadratic variation. This allows a pricing tool for European-style claims…
While deep learning gradually penetrates operational planning, its inherent prediction errors may significantly affect electricity prices. This letter examines how prediction errors propagate into electricity prices, revealing notable…
We consider a retailer who buys energy in the wholesale market and resells it to final consumers. The retailer has to decide when to intervene to change the price he asks to his customers, in order to maximize his income. We model the…
The large variability of renewable power sources is a central challenge in the transition to a sustainable energy system. Electricity markets are central for the coordination of electric power generation. These markets rely evermore on…