Abstract
A mobile energy storage system (MESS) is a localizable transportable storage system that provides various utility services. These services include load leveling, load shifting, losses minimization, and energy arbitrage. A MESS is also controlled for voltage regulation in weak grids. The MESS mobility enables a single storage unit to achieve the tasks of multiple stationary units at different locations. The MESS is connected to the grid at specific substations (or buses) known as MESS stations. This paper proposes an optimization algorithm for sizing and allocation of a MESS for multi-services in a power distribution system. The design accounts for load variation, renewable resources intermittency, and market price fluctuations. A realistic dynamic model for the MESS is adopted to consider the capacity and lifetime constraints. A detailed network power flow model is utilized to include voltage constraints, feeders, and transformers ampacity in the problem formulation. By considering all these constraints, the resulting sizing problem is a mixed-integer nonlinear problem. This paper presents the problem formulation and proposes a solution using a hybrid optimization technique. The adopted technique is based on the particle swarm algorithm and mixed-integer convex programming. A case study is conducted on a real 41-bus radial feeder to validate the proposed sizing technique, and investigate the MESS profitability to the system operator.
Highlights
The distribution power system structure is evolving to fit the increasing renewable energy sources penetration
The thesis presents planning and operation algorithms of energy storage in active distribution systems, whereas this paper focuses on the sizing and planning of mobile energy storage system (MESS) in more depth
The MESS is controlled to maximize the distribution company (Disco) profit and maintaining an acceptable power quality level
Summary
The distribution power system structure is evolving to fit the increasing renewable energy sources penetration. The work in [22] investigates MESS sizing for improving power system reliability and better RES integration. To the best of the authors’ knowledge, the problem of sizing MESS for multi-tasking in the power distribution system needs further investigation. The main contribution of this work is the development of a MESS sizing/allocation framework that maximizes the Disco profit by participating in multi-tasks. The thesis presents planning and operation algorithms of energy storage in active distribution systems, whereas this paper focuses on the sizing and planning of MESS in more depth.
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