A fuzzy logic energy management system of on-grid electrical system for residential prosumers

Dimitroulis, Pantelis; Alamaniotis, Miltiadis

doi:10.1016/j.epsr.2021.107621

Cited by 44 publications

(16 citation statements)

References 15 publications

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“…The nonlinear prediction model is a popular research direction, especially the combination of neural networks [57]. As for producers, it is evident that climate impacts the output of producers; however, the mechanism governing this phenomenon remains unclear [58] [59]. Combinatorial methods are also gaining increasing attention, such as the method combining machine learning and numerical weather prediction, which represents the integration of approximate physical models and statistical analyses.…”

Section: Predictionmentioning

confidence: 99%

Energy Management in Microgrid and Multi-microgrid

Xing¹,

Jia²

2023

Preprint

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<p>Considered as basic structures of next-generation energy system, environment-friendly and flexible microgrid (MG) systems are potential solutions to deal with stochastic renewable energy sources (RESs). The essence of management is to maximize the benefits of available resources through coordination and optimization, which also applies to energy systems. Adaptable energy management approaches provide the possibility to construct effective and various energy interaction. The purpose of this paper is to present a systematic review of energy management in MG systems, and further to propose an energy management model. Therefore, this paper first comprehensively reviews recent research studies on MG, particularly in the interconnected mode (called as multi-microgrid, MMG). Based on the analysis of relative literatures, a STEER (stability, touch, efficiency, evenness, and resilience) strategy is proposed and formulated from the perspective of energy utilization for energy management. Then, critical technologies in energy management are reviewed and summarized from the aspects of control, communication, optimization, prediction, and evaluation. Furthermore, energy management system is illustrated from the perspectives of system function, management framework and operation logic, based on a four-layer hierarchical architecture. Eight main prospects on the future trend of energy management in MG and MMG are also presented.</p>

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Section: Predictionmentioning

confidence: 99%

Energy Management in Microgrid and Multi-microgrid

Xing¹,

Jia²

2023

Preprint

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“…Dimitroulis and Alamaniotis [6] presents a fuzzy logic-based energy management system for residential prosumers, who produce electricity for their own consumption and sell it to the grid. The use of a mathematical model based on fuzzy logic allows reducing energy consumption costs and increasing profits from the sale of excess energy to the grid.…”

Section: Figure 1 Growth Of Res Capacitiesmentioning

confidence: 99%

Fuzzy logic in the decision-making tasks of connecting renewable energy sources into the electricity supply system

Stepanenko,

Zamulko,

Veremiichuk

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The Third and Fourth EU Energy Packages, as well as the Energy Strategy of Ukraine “Safety, Energy Efficiency, Competitiveness” until 2035, define the development of electricity production using renewable energy sources among the priorities of the energy sector. In this situation, the decision-making process on the integration of renewable energy sources into the electricity supply system is of particular importance. The article develops a fuzzy model for assessing the risks of connecting (integration) renewable energy sources to the power supply system. The toolkit, based on logical rules, allows modeling various connection options. The data obtained can then be used to set requirements for the parameters of the electrical installation at the stage of issuing technical specifications to the customer. The modeling results demonstrate the adequacy of the developed knowledge base and the possibility of using it to develop a methodology for the controlled and efficient connection of renewable energy sources to the power grid.

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“…[1], [7], [23], [33], [34], [37], [38] Self-Consumption [4], [5], [11], [24], [40], [41], [42], [43], [44] Microgrids [2], [3], [4], [5], [6], [11], [12], [13], [14], [15], [16], [40], [41], [42], [43], [44], [45] Policies and Regulation [8], [21], [22], [25], [27], [28], [30], [31], [32], [33], [34], [37], [39], [41], [45] Energy Communities [4], [9], [10], [17],…”

Section: Energy Statusmentioning

confidence: 99%

“…In [43], the implementation of an adaptive neuro-fuzzy inference system as a forecasting module inside prosumers is presented. In [44], a fuzzy logic energy management system (EMS) of on-grid electrical system for residential prosumers is presented proposing a climate-independent fuzzy logic EMS that integrates solar and wind generators, battery energy systems, electric vehicle (EV) load, dynamic electricity pricing, and tariffs, aiming to reduce the prosumer's electricity bill. The fuzzy controller strategy was compared with a simple rule-based system and a linear optimization approach, obtaining the lowest consumption cost, with the possibility of improving the control strategy based on the expert knowledge by adjusting the controller for more energy/cost savings, even more.…”

Section: Introductionmentioning

confidence: 99%

Optimal Fuzzy-Based Energy Management Strategy to Maximize Self-Consumption of PV Systems in the Residential Sector in Ecuador

Tapia¹,

Ulloa²,

Cunduri

et al. 2022

Energies

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This paper proposes a fuzzy-based energy management strategy (EMS) to maximize the self-consumption from a PV installation with an energy storage system (ESS) for the residential sector adapted to the Ecuadorian electricity market. The EMS includes two control levels: Energy management at the end-user level (Fuzzy-based EMS and optimized by genetic Algorithm) and Energy management at the distribution grid level (Fuzzy-based EMS). Both strategies aim to maximize the use of the energy generated at home (taking into account the local solar generation profile), fulfilling the loads’ demand and injecting the energy surplus into the main grid to be economically compensated. Additionally, this paper presents economical modeling according to the electricity market in Ecuador. The main results showed a cost reduction in the electricity bill up to 83.64% from the base case (residential consumption without a PV system). In the scenario of a community electricity market (still not contemplated under the Ecuadorian electricity law), the potential economic savings may be more than double compared to the exact case but only with a self-consumption system.

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A fuzzy logic energy management system of on-grid electrical system for residential prosumers

Cited by 44 publications

References 15 publications

Energy Management in Microgrid and Multi-microgrid

Energy Management in Microgrid and Multi-microgrid

Fuzzy logic in the decision-making tasks of connecting renewable energy sources into the electricity supply system

Optimal Fuzzy-Based Energy Management Strategy to Maximize Self-Consumption of PV Systems in the Residential Sector in Ecuador

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