الفهرس 
Microgrid DefinitionsOnly 14 pages are availabe for public view
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Abstract
Recently, much attention has been paid to means of developing centralized, producer-controlled traditional power grids to be smarter self-managing and reliable grids that can produce, transmit, and use energy effectively, along with strengthened plans for environmental protection and pollution control. Also, the creation of economic incentives and increased usage of consumer-interactive renewable energy sources (RESs) remain the main solutions to transit away from traditional high-carbon energy sources. In this regard, a microgrid (MG) is projected as a localized consumer-interactive distribution network construction within the smart grid community, to achieve a low-carbon society with reduced greenhouse gas emissions, while taking into account the local-generation properties, variability in the generation inputs and economic aspects. In response to environmental and social initiatives, as well as technical and economic development, energy generation from renewable energy sources (RESs) is rapidly developing across the world to improve the performance of MG and increase the share of RES in the world energy production.
In this regard, energy storage (ES) technologies are the key enablers for reliable use of renewables because they introduce many benefits for microgrid. However, the choice of a suitable ES technology depends on several techno-economic metrics, which require the decision-maker to investigate the applicability of the technology and whether it offers promising benefits or not. Hence, this PhD thesis presents an ES cost model that considers long-term, medium-term, and short-term ES applications, technologies and technical characteristics in an integrated framework that consider the ES technical and economic characteristics supported by in-market insight, including capital costs of the technologies; operation and maintenance costs; replacement costs during the lifetime of the system; and disposal and recycling costs, based on the current ES costs. Two key metrics, namely the annualized life cycle cost of storage (LCCOS) and the levelized cost of energy (LCOE), are used to make proper ES operational choices while complying with their technical and operational performance limits. Further, a sensitivity analysis of the governing factors that affect the storage cost is presented to introduce a powerful decision tool to empower techno-economic assessment of ES systems (ESS) using the proposed cost models.
During this PhD work, a comprehensive study of the economical energy management (EM) of a grid-connected MG will be presented by considering the all battery characteristics such as initial charge, depth of discharge and numbers of charging/discharging cycles since they have a significant influence on the accuracy of the energy management of MGs. So, first, this study presents the economic analysis and optimal EM of a grid-connected MG that comprises renewable energy resources and different battery storage technologies with different characteristics to minimize the total operating cost of the system. Several constraints are considered, such as the output power limits of the distributed generators, the limits of power imported from or exported to the main grid, load balance and other sets of battery storage constraints. The general algebraic modeling system (GAMS) is used to solve the deterministic optimization problem. Second, stochastic optimization is used to solve the deterministic problem with market price uncertainty. Third, robust optimization using information gap decision theory is presented to model the electric load uncertainty. The validity and effectiveness of the proposed solution are explained by comparing the results obtained by GAMS to the results obtained by other optimization techniques presented in the literature.
Eventually, This PhD thesis formulates a two-stage optimization framework to improve the performance of grid-connected MG. In the first stage, the optimal allocation decisions of ESS are prepared to enhance the self-consumption rate of all RESs in the MG. Then, in the second stage, the optimal operation strategy is prepared for the MG with considered the results of the first stage to achieve the minimization of the total operation cost of the MG. The optimal operation strategy takes the charge-discharge balance as the criterion, considers the battery storage (BS) constraints and the MG constraints, and aims to minimize the operation cost of the MG by maximizing the benefits of the BS operation.