Abstract
Efficient supply of electric energy, maintaining power quality, and addressing intermittency of renewable energy and unpredictable demand fluctuations are challenges of a modern power grid. An individual energy storage technology seldom provides all the desired characteristics expected. A Hybrid Energy Storage System (HESS) including different types of energy storage systems can address these challenges. In this work a new formulation and algorithm was developed that optimally designs a grid-scale HESS for desired performances such as peak load shaving and power demand curve smoothening at the least capital cost. The proposed HESS comprised of a combination of Lithium Ion batteries, Flywheels, and Ultracapacitor based Energy Storage Systems. Real and synthetic power demand dataset representing different types of demand fluctuations were used in the analysis. The proposed formulation and algorithm was able to optimally size HESS such that it costs the least while performing in the desired manner.
Highlights
3.3 Objective Function and Constraints3.4 Chapter Summary
In Data Case 1, one-day Ontario power demand data were used and in the Data Case 2 power demand data were created with various magnitude of power demand fluctuation for slow and fast demand change cycles
Three optimization tools ‘Fmincon’, ‘Patternsearch’ and ‘Genetic Algorithm’ in MATLAB have been utilized to determine the optimum solution of the optimization problem
Summary
3.3 Objective Function and Constraints3.4 Chapter Summary. 4.2 Selection of MATLAB Solvers: ‘Fmincon’, ‘Patternsearch’ and ‘Genetic Algorithm’4.3 Optimization Problem Solution with Real Power Demand Data4.3.1 Algorithm for Data Case 14.3.2 Power Demand Data for Data Case 14.3.3 Effects of Different Parameters for Data Case 14.4 Optimization Problem Solution for Power Demand Data Created withDifferent Magnitude of Demand Fluctuations: Data Case 24.4.1 Power Demand Data for Data Case 24.4.2 Algorithm for Data Case 24.4.3 Effects of Different Parameters. The main challenges of the modern power systems that need to be addressed are: high cost for peak generation, intermittency of renewable energy, unpredictable demand fluctuation, frequency regulation, fossil fuel dependency, etc. Using hybrid energy storages systems (HESSs) that consist of various different types of energy storage elements is a promising and doable solution This enables a cost-effective (in the long run) and energy-efficient approach by fully exploiting the strengths of different energy storage technologies to compensate each other’s drawbacks [Kim, 2012] through appropriate charge management processes that includes charge replacement, allocation, and migration [Wang, 2011; Xie, 2011; Xie, 2012]. HESS increases the energy efficiency of the grid by proper energy management, peak shaving, load balancing, and so on [Mirhoseini, 2011; Shin, 2011] It removes the intermittency of renewable sources by storing the excess generated energy to extract and utilize the maximum power from the sources [Kim, 2010]
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