Abstract:Battery energy storage systems (BESSs) are key components in efficiently managing the electric power supply and demand in microgrids. However, the BESSs have issues in their investment costs and operating lifetime, and thus, the optimal sizing of the BESSs is one of the crucial requirements in design and management of the microgrids. This paper presents a problem framework and its solution method that calculates the optimal size of the BESSs in a microgrid, considering their cooperative operations with the oth… Show more
“…In order to fulfil the strategic objectives of "carbon peaking" and "carbon neutralisation," the new energy, represented by wind and solar power, has been steadily replacing the traditional power production unit and has started to access a substantial number of microgrids [1][2][3]. Multiple power sources and loads may operate effectively and dependably inside a network thanks to microgrids.…”
The most effective and economical power dispatching for microgrids is incorporated into the new power system optimisation, it is essential for reducing energy use and pollution. The microgrid should make money and deliver power that meets the absolute minimal requirements. In this study, we propose a combined optimisation approach for a distributed energy system with windphotovoltaic load storage. The cost of production, the cost of discharge, the cost of acquisition, and the revenue from the sale of energy are all taken into consideration in this model. The relevant particle swarm optimization-based model solution algorithm is also supplied. The efficiency of the suggested model and algorithm is further demonstrated. In this research, Using a project case study, the joint optimal method for a distributed energy system with wind-photovoltaic load storage is examined and addressed.. It also presents the most practical and affordable power dispatching strategies under various scenarios.
“…In order to fulfil the strategic objectives of "carbon peaking" and "carbon neutralisation," the new energy, represented by wind and solar power, has been steadily replacing the traditional power production unit and has started to access a substantial number of microgrids [1][2][3]. Multiple power sources and loads may operate effectively and dependably inside a network thanks to microgrids.…”
The most effective and economical power dispatching for microgrids is incorporated into the new power system optimisation, it is essential for reducing energy use and pollution. The microgrid should make money and deliver power that meets the absolute minimal requirements. In this study, we propose a combined optimisation approach for a distributed energy system with windphotovoltaic load storage. The cost of production, the cost of discharge, the cost of acquisition, and the revenue from the sale of energy are all taken into consideration in this model. The relevant particle swarm optimization-based model solution algorithm is also supplied. The efficiency of the suggested model and algorithm is further demonstrated. In this research, Using a project case study, the joint optimal method for a distributed energy system with wind-photovoltaic load storage is examined and addressed.. It also presents the most practical and affordable power dispatching strategies under various scenarios.
“…[25], two meta-heuristic algorithms, namely genetic algorithms (GA) and particle swarm optimization (PSO), are used for optimally siting and sizing of BESS in distribution networks in order to mitigate the effects of RES fluctuations on energy supply reliability and quality. Meta-heuristics are explored as well in [26], where the BESS sizing problem is solved based on a bi-level hybrid PSO-quadratic programming algorithm, which considers the cooperative operations of controllable components in a microgrid. In terms of resilience-related goals, authors of [27] investigate design aspects in low-voltage grids focusing on various BESS capacities and voltage level control with active power regulation in energy communities, while [13] proposes a centralized shared energy storage capacity optimization model that aims to minimize the operational costs in resilience microgrids using a two-layered approach.…”
As climate changes intensify the frequency of severe outages, the resilience of electricity supply systems becomes a major concern. In order to simultaneously combat the climate problems and ensure electricity supply in isolated areas, renewable energy sources (RES) have been widely implemented in recent years. However, without the use of energy storage, they show low reliability due to their intermittent output. Therefore, this article proposes a methodology to achieve the optimal sizing of an energy storage system (ESS) to ensure predefined periods of safe operation for an ensemble consisting of multiple loads, renewable energy sources and controllable generators, located in a remote microgrid. In this regard, a mixed integer linear programming (MILP) model has been proposed to reduce the outages impact of critical loads by calculating the optimal ESS capacity and defining the proper resources management within the off-grid microgrid, while ensuring a cost-effective operation of its components.
“…According to ref. [17], BESSs have issues with investment costs and operating lifetimes; therefore, adequate BESS sizing is crucial for microgrid design and administration. This article proposed a problem structure and solution approach for calculating the optimal size of BESSs in a microgrid using the binary particle swarm optimization (BPSO) combined with a quadratic programming algorithm for two objectives-investment cost and operating cost.…”
This paper develops a multi-objective co-design optimization framework for the optimal sizing and selection of battery and power electronics in hybrid battery energy storage systems (HBESSs) connected to the grid. The co-design optimization approach is crucial for such a complex system with coupled subcomponents. To this end, a nondominated sorting genetic algorithm (NSGA-II) is used for optimal sizing and selection of technologies in the design of the HBESS, considering design parameters such as cost, efficiency, and lifetime. The interoperable framework is applied considering three first-life battery cells and one second-life battery cell for forming two independent battery packs as a hybrid battery unit and considers two power conversion architectures for interfacing the hybrid battery unit to the grid with different power stages and levels of modularity. Finally, the globally best HBESS system obtained as the output of the framework is made up of LTO first-life and LFP second-life cells and enables a total cost of ownership (TCO) reduction of 29.6% compared to the baseline.
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