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This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system. • An efficient energy storage system is essential for managing intermittent energy supply. • The fuel cell can generate DC power by combining hydrogen with oxygen. • The amount of power generated by a PV panel depends on temperature and solar radiation intensity. • Deterministic rule-based controllers operate based on pre-defined rules. • Energy Management System coordinate the flow of power between different components. [ABSTRACT FROM AUTHOR]

Economic, technological, and environmental causes are moving energy toward smart distribution networks. The change from fossil fuels to renewable energy sources is extremely environmentally friendly in both the building and transport sectors. Microgrids could be efficiently used in remote areas utilizing renewable energy resources for supplying different energy demands namely power, heat and cold. This paper presents a mixed-integer linear programming (MILP) model for optimizing planning and sizing decisions in microgrids connected to main grid. Planning decisions the amount of generation of each distributed generation (DG) technology and the amount of power transmission to other nodes. Also, sizing of different DGs including photovoltaic and combined heat and power facilities are performed by the proposed model. According to the results, the model is able to optimize sizing and planning decisions in grid-connected microgrids. [ABSTRACT FROM AUTHOR]

Due to increasing amounts of energy being supplied by intermittent renewable energy sources, future energy systems need to be able to react flexibly to sudden changes. To address this challenge, a large body of research is devoted to improving the utilization of energy flexibility of various types of energy resources on the supply and demand side. This is commonly done by applying mathematical models. The objective of this paper is to review such models and identify common modeling approaches used to quantify and optimize the use of flexible energy resources. The literature review is conducted systematically, encompassing 215 publications that feature 694 models of different energy resources. The main distinction of this work, in comparison to other reviews on the topic of energy flexibility lies in its focus on the mathematical formulation of models of energy resources and the quantification of the models' level of detail. The aim is to identify common modeling approaches and the corresponding research problems they address. The review shows that the majority of research efforts are directed towards the management and optimization of distributed energy resources. The most commonly employed modeling approach involves abstract black-box models with limited levels of detail. Linear programming and meta-heuristics are frequently used to optimize energy flexibility. A critical reflection of the current common practice is conducted and recommendations for future research are formulated. [Display omitted] • Literature review of 215 reports presenting model approaches for energy flexibility. • Categories of research problems identified and deduction of two main research focuses. • Presenting models of common energy resources classified into different model types. • Mostly low level of detail seen in modeling energy flexibility. • Optimization models are used to represent and quantify flexibility. [ABSTRACT FROM AUTHOR]

Increasing attention has recently been drawn to energy consumption in manufacturing plants. Facing the challenges from reducing emissions coupled with rising raw material prices and energy costs, manufacturers are trying to balance the energy usage strategy among the total energy consumption, economy, and environment, which can be self-conflicting at times. In this paper, energy systems in manufacturing environments are reviewed, and the current status of onsite energy system and renewable energy usage are discussed. Single objective and multicriteria optimization approaches are effectively formulated for making the best use of energy delivered to the production processes. Energy supply operation suggestions based on the optimization results are obtained. Finally, an example from an automotive assembly manufacturer is described to demonstrate the energy usage in the current manufacturing plants and how the optimization approaches can be applied to satisfy the energy management objectives. According to the optimization results, in an energy oriented operation, it takes 35% more in monetary cost; while in an economy oriented operation, it takes 17% more in megawatt hour energy supply and tends to rely more on the inexpensive renewable energy. [ABSTRACT FROM AUTHOR]