Pinned Repositories
Analysis_FoodSafetyScores
Project 1- Data 100- Analysis of Restaurant Food Safety Scores
Batch-Reinforcement-Learning
This project finds the best policy for three different Markov decision processes given sampled transitions, each consisting of a state, action, reward, and next state without exploration
Bayesian-Structure-Learning
Project to find Bayesian Network Structures that best fit given some data based on the Bayesian Score of the graph.
Data-Science-Projects
Data Science Projects covering Spam Ham Email Classification, Analysis of Donald Trump's Tweets, EDA, Sampling Error, Gradient Descent, PCA, Logistic Regression and More
DCFC_Battery_Optimization
docs
Source code for the Streamlit Python library documentation
Energy-Conversion-Principles-Projects
Projects related to modeling Solar Hybrid Power, Wind Turbines, Solar Collector Systems, and Gas Turbine Evaluaiton
Energy_Systems_and_Control-Projects
Projects related to Energy Systems and Control covering Flight Path Optimization, Battery Modeling, State Estimation, Optimal Economic Dispatch of Distribution, Forecasting Electricity Power Consumption, Optimal PHEV Energy Management
Grid_Scale_Energy_Storage_Q_Learning
Final Project for AA 228: Decision-Making under Uncertainty Abstract: Grid-scale energy storage systems (ESSs) are capable of participating in multiple grid applications, with the potential for multiple value streams for a single system, termed "value-stacking". This paper introduces a framework for decision making, using reinforcement learning to analyze the financial advantage of value-stacking grid-scale energy storage, as applied to a single residential home with energy storage. A policy is developed via Q-learning to dispatch the energy storage between two grid applications: time-of-use (TOU) bill reduction and energy arbitrage on locational marginal price (LMP). The performance of the dispatch resulting from this learned policy is then compared to several other dispatch cases: a baseline of no dispatch, a naively-determined dispatch, and the optimal dispatches for TOU and LMP separately. The policy obtained via Q-learning successfully led to the lowest cost, demonstrating the financial advantage of value-stacking.
ML_Electricity_Demand_US_Covid19
deep-daya's Repositories
deep-daya/Energy_Systems_and_Control-Projects
Projects related to Energy Systems and Control covering Flight Path Optimization, Battery Modeling, State Estimation, Optimal Economic Dispatch of Distribution, Forecasting Electricity Power Consumption, Optimal PHEV Energy Management
deep-daya/Grid_Scale_Energy_Storage_Q_Learning
Final Project for AA 228: Decision-Making under Uncertainty Abstract: Grid-scale energy storage systems (ESSs) are capable of participating in multiple grid applications, with the potential for multiple value streams for a single system, termed "value-stacking". This paper introduces a framework for decision making, using reinforcement learning to analyze the financial advantage of value-stacking grid-scale energy storage, as applied to a single residential home with energy storage. A policy is developed via Q-learning to dispatch the energy storage between two grid applications: time-of-use (TOU) bill reduction and energy arbitrage on locational marginal price (LMP). The performance of the dispatch resulting from this learned policy is then compared to several other dispatch cases: a baseline of no dispatch, a naively-determined dispatch, and the optimal dispatches for TOU and LMP separately. The policy obtained via Q-learning successfully led to the lowest cost, demonstrating the financial advantage of value-stacking.
deep-daya/Energy-Conversion-Principles-Projects
Projects related to modeling Solar Hybrid Power, Wind Turbines, Solar Collector Systems, and Gas Turbine Evaluaiton
deep-daya/Data-Science-Projects
Data Science Projects covering Spam Ham Email Classification, Analysis of Donald Trump's Tweets, EDA, Sampling Error, Gradient Descent, PCA, Logistic Regression and More
deep-daya/ML_Electricity_Demand_US_Covid19
deep-daya/Analysis_FoodSafetyScores
Project 1- Data 100- Analysis of Restaurant Food Safety Scores
deep-daya/Batch-Reinforcement-Learning
This project finds the best policy for three different Markov decision processes given sampled transitions, each consisting of a state, action, reward, and next state without exploration
deep-daya/Bayesian-Structure-Learning
Project to find Bayesian Network Structures that best fit given some data based on the Bayesian Score of the graph.
deep-daya/DCFC_Battery_Optimization
deep-daya/docs
Source code for the Streamlit Python library documentation
deep-daya/ELENG134-UC-Berkeley
deep-daya/Java-Projects
deep-daya/keras
Deep Learning for humans
deep-daya/Tetrahedral_Occupation_Li_Inorganic_Crystals
Final Project for Data100: Providing insight for tendency of elements to occupy a given tetrahedral site in inorganic crystals
deep-daya/Wind-Temperature-Modeling
CS 231N Project