More Like this

1. Distribution-level markets under high renewable energy penetration

   https://doi.org/10.1145/3538637.3538846  

   Ju, Peizhong; Lin, Xiaojun; Huang, Jianwei (June 2022, Thirteenth ACM International Conference on Future Energy Systems (ACM e-Energy 2022))

   We study the market structure for emerging distribution-level energy markets with high renewable energy penetration. Renewable generation is known to be uncertain and has a close-to-zero marginal cost. In this paper, we use solar energy as an example of such zero-marginal-cost resources for our focused study. We first show that, under high penetration of solar generation, the classical real-time market mechanism can either exhibit significant price-volatility (when each firm is not allowed to vary the supply quantity), or induce price-fixing (when each firm is allowed to vary the supply quantity), the latter of which leads to extreme unfairness of surplus division. To overcome these issues, we propose a new rental-market mechanism that trades the usage-right of solar panels instead of real-time solar energy. We show that the rental market produces a stable and unique price (therefore eliminating price-volatility), maintains positive surplus for both consumers and firms (therefore eliminating price-fixing), and achieves the same social welfare as the traditional real-time market. A key insight is that rental markets turn uncertainty of renewable generation from a detrimental factor (that leads to price-volatility in real-time markets) to a beneficial factor (that increases demand elasticity and contributes to the desirable rental-market outcomes). 

   more » « less
2. The Effects of Climate Change on Interregional Electricity Market Dynamics on the U.S. West Coast

   https://doi.org/10.1029/2021EF002400  

   Hill, Joy; Kern, Jordan; Rupp, David_E; Voisin, Nathalie; Characklis, Gregory (December 2021, Earth's Future)

   Abstract The United States (U.S.) West Coast power system is strongly influenced by variability and extremes in air temperatures (which drive electricity demand) and streamflows (which control hydropower availability). As hydroclimate changes across the West Coast, a combination of forces may work in tandem to make its bulk power system more vulnerable to physical reliability issues and market price shocks. In particular, a warmer climate is expected to increase summer cooling (electricity) demands and shift the average timing of peak streamflow (hydropower production) away from summer to the spring and winter, depriving power systems of hydropower when it is needed the most. Here, we investigate how climate change could alter interregional electricity market dynamics on the West Coast, including the potential for hydroclimatic changes in one region (e.g., Pacific Northwest (PNW)) to “spill over” and cause price and reliability risks in another (e.g., California). We find that the most salient hydroclimatic risks for the PNW power system are changes in streamflow, while risks for the California system are driven primarily by changes in summer air temperatures, especially extreme heat events that increase peak system demand. Altered timing and amounts of hydropower production in the PNW do alter summer power deliveries into California but show relatively modest potential to impact prices and reliability there. Instead, our results suggest future extreme heat in California could exert a stronger influence on prices and reliability in the PNW, especially if California continues to rely on its northern neighbor for imported power to meet higher summer demands. 

   more » « less
3. Pricing Energy in the Presence of Renewables

   https://doi.org/10.23919/ACC.2018.8431899  

   Zeinalzadeh, Ashkan; Ghavidel, Donya; Gupta, Vijay (June 2018, 2018 Annual American Control Conference (ACC))

   The intermittent nature of renewable energy generation implies that renewable producers rely on non-renewable producers to ensure the aggregate power delivered meets the promised quality of service. Therefore, the intermittent nature of renewable energy generation affects the committed power and market price of energy. We consider an electricity market where renewable and non-renewable generators bid by proposing their asking price per unit of energy to an independent system operator (ISO). The ISO solves a dispatch optimization problem to minimize the cost of purchased energy on behalf of the consumers. We incorporate the notion of net-load variance using the Conditional Value-at-Risk (CVAR) measure in the dispatch optimization problem to ensure that the generators are able to meet the load within a desired confidence level. We analytically derive the market clearing price of energy and dispatched powers as a function of CVAR and show that a higher penetration of renewable energies may increase the market clearing price of energy. Finally, we present descriptive simulations to illustrate the impact of renewable energy penetration on the market price of energy. 

   more » « less
4. Sensitivity analysis of convergence bids in nodal electricity markets

   https://doi.org/10.1109/NAPS.2017.8107412  

   Kohansal, Mahdi; Mohsenian-Rad, Hamed (November 2017, IEEE PES North American Power System Symposium)

   Recent reports from Independent System Operators (ISOs) have raised some concerns about the impact of convergence bids (CBs) on nodal electricity markets. In particular, in some cases, there are concerns about cases where CBs are profitable for some market participants without increasing market efficiency significantly or even decreasing market efficiency. The latter occurs when CBs create price divergence instead of price convergence across the day-ahead and real-time markets. Accordingly, in this paper, we investigate the sensitivity of nodal electricity market price to CBs and seek to build an analytical foundation to explain under what conditions placing a CB at a bus in a nodal electricity market can create price divergence at that bus. Illustrative test cases are discussed to provide intuitions and engineering implications of the results on sensitivity analysis. 

   more » « less
5. Stock price prediction using sentiment Based LSTM: S&P500 vs Reddit posts

   Richard-Ojo, O; Wimmer, H. (April 2024, The Proceedings of IEMTRONICS 2024)

   Phillip Bradford, S. Andrew (Ed.)

   The stock market is as volatile as it is unpredictable, the unstable nature of the stock market results in fluctuations in stock prices and invariably, the market performance of stocks. Understanding the underlying factors that contribute to the volatility of the stock market, which has its consequences on stock prices, has become important to researchers and investors alike. Some of the methods that researchers have used in the past as a gauge for understanding market performance include analyzing economic conditions, understanding company performance, following geopolitical events and market trends. To contribute to the vast research field of stock price predictions and the challenge of understanding stock price fluctuations, this study will aim to find a relationship between human sentiments on the social media platform, Reddit, and the S&P 500 stock index. In this study, we will analyze posts from five subreddits that typically discuss the stock market and stock price fluctuations. This will form the first part of our dataset. Historical stock prices for the S&P 500 index will be obtained from Yahoo Finance. This will form our final dataset. Using VADER (Valence aware dictionary and sentiment reasoner), we will extract the sentiments within the five subreddits and categorize them into positive and negative sentiments. The historical stock prices from Yahoo finance will be matched with the aggregate sentiments for each day and this data passed through the LSTM model for training. Our findings provide strong evidence of social media’s impact on stock price predictions. 

   more » « less