scholarly journals Learning Spatiotemporal Dynamics in Wholesale Energy Markets with Dynamic Mode Decomposition

2020 ◽  
Author(s):  
Clay T. Elmore ◽  
Alexander Dowling
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Markets ◽  
Dynamic Mode Decomposition ◽  
Machine Learning Techniques ◽  
Dynamic Mode ◽  
Forecasting Methods ◽  
Mode Decomposition ◽  
Storage Technologies

Energy markets facilitate the balancing of electricity generation (supply) and demand while ensuring non-discriminatory access. Understanding energy market dynamics is essential to improving grid efficiency and resilience and optimizing the development of new energy conversion and storage technologies. Accurate energy price forecasts are essential for many energy storage technologies to be profitable from price arbitrage. In this paper, we apply the novel spatial-temporal dimensionality reduction method of Dynamic Mode Decomposition (DMD) to forecast 6587 locational marginal prices in the California Independent System Operator (CAISO) on the Day-Ahead Market (DAM). DMD is a promising equation-free modeling technique in systems with inherent periodic tendencies in time such as financial markets and fluid dynamics. Yet we show, for the first time, that DMD cannot reliably forecast day-ahead energy prices due to the so-called standing wave problem. Instead, we find Augmented DMD (ADMD) overcomes these limitations is a fast and accurate price forecaster. We benchmark DMD, ADMD, and backcasting forecasting methods for optimal price arbitrage with an energy storage system. We find, using ADMD, a market-connected energy storage system can capture up to 92% of allowable revenues in rolling horizon simulations. Lastly, we show ADMD is up to 1000-times faster than time-series forecasting methods (i.e., ARIMA) which requires orders of magnitude less data than deep/machine learning techniques.

scholarly journals Effect of Prediction Error of Machine Learning Schemes on Photovoltaic Power Trading Based on Energy Storage Systems

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1249 ◽  
Author(s):  
Kuk Bae ◽  
Han Jang ◽  
Bang Jung ◽  
Dan Sung
Keyword(s):  
Machine Learning ◽  
Energy Storage ◽  
Output Power ◽  
Storage System ◽  
Weather Conditions ◽  
Energy Storage System ◽  
Energy Markets ◽  
Prediction Errors ◽  
Power Prediction ◽  
Power Trading

Photovoltaic (PV) output power inherently exhibits an intermittent property depending on the variation of weather conditions. Since PV power producers may be charged to large penalties in forthcoming energy markets due to the uncertainty of PV power generation, they need a more accurate PV power prediction scheme in energy market operation. In this paper, we characterize the effect of PV power prediction errors on energy storage system (ESS)-based PV power trading in energy markets. First, we analyze the prediction accuracy of two machine learning (ML) schemes for the PV output power and estimate their error distributions. We propose an efficient ESS management scheme for charging and discharging operation of ESS in order to reduce the deviations between the day-ahead (DA) and real-time (RT) dispatch in energy markets. In addition, we estimate the capacity of ESSs, which can absorb the prediction errors and then compare the PV power producer’s profit according to ML-based prediction schemes with/without ESS. In case of ML-based prediction schemes with ESS, the ANN and SVM schemes yield a decrease in the deviation penalty by up to 87% and 74%, respectively, compared with the profit of those schemes without ESS.

Energy Storage Technologies in Renewable Energy Electricity Generation System

2012 ◽  
Vol 462 ◽  
pp. 225-232 ◽  
Author(s):  
Rui Cao ◽  
Zi Long Yang
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage System ◽  
Clean Energy ◽  
Energy Generation ◽  
Energy Storage System ◽  
Generation System ◽  
Storage Technologies ◽  
Renewable Energy Generation ◽  
Generation Technology

Today，there is a continuous need for more clean energy, this need has facilitated the increasing of distributed generation technology and renewable energy generation technology. In order to ensure the supply of renewable energy generation continuously and smoothly in distributed power generation system, need to configure a amount of energy storage system for storing excess power generated. This article outlines some energy storage technologies which are used in power systems in the current and future, summarizes the working principles and features of several storage units, provides the basis for the design of energy storage system.

scholarly journals Optimization of Microgrid Battery Capacity using PSO with Considering Islanding Operation

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Ayu Sintianingrum, Khairudin, Lukmanul Hakim
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Pso Algorithm ◽  
Energy Storage System ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Battery Capacity ◽  
Effective System ◽  
Islanding Operation ◽  
Storage Technologies

Electrical is used for various activities in all sectors. Rapid increase of electricity demand recently, makes it necessary to have an even more efficient method for generating electricity. Renewable energy and the microgrid provides an integrated and alternative solution for electricity generation. In microgrid systems, energy storage devices are one of important aspects. Batteries are one kind of the energy storage technologies widely used in power system and hence, their suitable capacity must be determined in order to develop an effective system installation. In this research, sizing optimization of battery capacity is modeled as a minimization of microgrid battery capacity using the Particle Swarm Optimization/PSO algorithm with considering islanding operation of the system for effective battery installation. Results show that optimal battery capacity can be obtained and the developed computational model gives satisfactory results for the system under study.   Keywords: Battery, microgrid, energy storage system, PSO algorithm

scholarly journals Renewable Energy: Pumped Hydro Energy Storage System (Water Bank)

2019 ◽  
Vol 8 (4) ◽  
pp. 3846-3850
Keyword(s):  
Energy Storage ◽  
Electricity Markets ◽  
Storage Capacity ◽  
Storage System ◽  
Energy Storage System ◽  
Future Technology ◽  
Energy Storage Capacity ◽  
Electric Station ◽  
Storage Technologies ◽  
System Water

It gives an impression of vacant electrical storage technologies, methods to compute cost and profits streams, along with future technology advancements. Moving water between two reservoirs by turbine or a propeller at different elevations, that generates the energy works like a conventional hydro electric station. Pumped hydro storage reports for approximately 96% of universal energy storage capacity. It provides an outline of the mechanisms by which these pumped hydro plants interrelate with their individual electricity markets in the countries with the major predicted growth of maze-scale energy storage. Variablespeed and ternary PHS systems allow for faster and wider operating ranges, providing additional flexibility at all timescales, enabling high penetrations of VRE at lower system costs.

Overview on Key Technologies of Grid-Connected Wind Power Based on Energy Storage

2012 ◽  
Vol 608-609 ◽  
pp. 668-672
Author(s):  
Gui Xiong He ◽  
Zhe Jiang ◽  
Li Min Jiang ◽  
Hua Guang Yan ◽  
Xiao Bing Yang
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Wind Farm ◽  
Low Voltage ◽  
Storage System ◽  
Wind Farms ◽  
Energy Storage System ◽  
System Stability ◽  
Stable Operation ◽  
Storage Technologies

In order to promote the development of wind power and accelerate the efficient use of new energy sources, countries have brought energy storage systems into grid-connected wind farms to achieve efficient and stable operation of the wind power plant. This paper recounts the latest development status and trend of wind power at home and abroad, and introduces the principle of power conversion between energy storage system and wind farm. Based on the existing research results, it analyses power system stability related to wind power, low voltage ride-through ability of wind turbine, wind power penetration limit, as well as power quality issues. It also describes the new ideas about how to use energy storage technologies to solve the problems faced by the wind power.

Energy Storage System

2009 ◽  
Vol 147-149 ◽  
pp. 416-420
Author(s):  
Tomasz Siostrzonek ◽  
Stanisław Piróg
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Storage System ◽  
Energy Storage System ◽  
Flywheel Energy Storage ◽  
Storage Technologies

In this article the storage systems: capacitors, batteries and flywheel energy storage are described. The flywheel energy storage will be described precisely and compared with other energy storage technologies.

Sign in / Sign up

Export Citation Format

Share Document