The Selection of Optimal Structure for Stand-Alone Micro-Grid Based on Modeling and Optimization of Distributed Generators

Ma, Xiaoxu; Li, Shuqin; Liu, Hongtao; Zhao, Sipeng

doi:10.1109/access.2022.3164514

Cited by 21 publications

(9 citation statements)

References 55 publications

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“…Biomass generation works on the principle that this biogas acts as combusting fuel, and the thermal energy is converted to mechanical energy through internal combustion eventually converting into electrical energy through a turbine. The relation between biofuel and output power is described in Equation ( 9) [41]:…”

Section: Modeling Of Biomass Generation Systemmentioning

confidence: 99%

Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources

et al. 2023

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The availability of sustainable, efficient electricity access is critical for rural communities as it can facilitate economic development and improve the quality of life for residents. Isolated microgrids can provide a solution for rural electrification, as they can generate electricity from local renewable energy sources and can operate independently from the central grid. Residential load scheduling is also an important aspect of energy management in isolated microgrids. However, effective management of the microgrid’s energy resources and load scheduling is essential for ensuring the reliability and cost-effectiveness of the system. To cope with the stochastic nature of RERs, the idea of an optimal energy management system (EMS) with a local energy transactive market (LETM) in an isolated multi-microgrid system is proposed in this work. Nature-inspired algorithms such as JAYA (Sanskrit word meaning victory) and teaching–learning based optimization algorithm (TLBO) can get stuck in local optima, thus reducing the effectiveness of EMS. For this purpose, a modified hybrid version of the JAYA and TLBO algorithm, namely, the modified JAYA learning-based optimization (MJLBO), is proposed in this work. The prosumers can sell their surplus power or buy power to meet their load demand from LETM enabling a higher load serving as compared to a single isolated microgrid with multi-objectives, resulting in a reduced electricity bill, increased revenue, peak-average ratio, and user discomfort. The proposed system is evaluated against three other algorithms TLBO, JAYA, and JAYA learning-based optimization (JLBO). The result of this work shows that MJLBO outperforms other algorithms in achieving the best numerical value for all objectives. The simulation results validate that MJLBO achieves a peak-to-average ratio (PAR) reduction of 65.38% while there is a PAR reduction of 51.4%, 52.53%, and 51.2% for TLBO, JLBO, and JAYA as compared to the unscheduled load.

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Section: Modeling Of Biomass Generation Systemmentioning

confidence: 99%

Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources

et al. 2023

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“…In [27], a PT bidding strategy is proposed for a storage system in ancillary services for frequency regulation. Different combinations of DGs for utilizing AC, DC, and hybrid MGs in a multiobjective problem are proposed in [28]. The authors of this article focused on the existing uncertainties, which include solar radiation, wind speed, temperature, and consumer load.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…Some papers neglect the optimal operation indices for simplicity [23], and others do not consider the MG's operation formulation to focus on other concepts [24]- [26]. In [28]- [30], the optimal operation management of an MG is modeled without DR and the electricity market. In [41], the characteristics of the real-time market are added to the MG's operation model.…”

Section: B Literature Reviewmentioning

confidence: 99%

Game Theory-Based Bidding Strategy in the Three-Level Optimal Operation of an Aggregated Microgrid in an Oligopoly Market

et al. 2022

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This paper proposes a new framework for the optimal operation of a microgrid aggregator (MGA) that participates in an oligopoly electricity market. This aggregator obtains an optimal bidding (power and price) strategy for a multigrid (MG) system, i.e., a community MG. Consequently, the granted quantity, i.e., power in the electricity market, is deployed to optimally schedule the MG's resources to meet demand. As such, as per three-level optimization, the independent system operator (ISO) clears the market with the goal of maximizing the social welfare in the first stage and determining the hourly market price as well as players' credited power. In the second-level optimization process, the players select the optimal coefficient supply function equilibrium according to the power granted from the market. In third-level optimization, an optimal scheduling for MGs' resources and demand would be obtained according to the won power in the market to maximize the aggregator profit. In addition, a price-taker MGA is simulated for comparison with the price-maker MGA to highlight the advantage of the proposed technique. Furthermore, a bidding strategy based on game theory is proposed to obtain the optimal price and power of the oligopoly market players and maximize all players' profits. Finally, a test system including three generators is created to evaluate the performance of the devised bidding strategy. The results show that the proposed bidding strategy can optimally calculate the focal point of the Nash equilibrium (NE) in the oligopoly electricity market.INDEX TERMS game theory, microgrid operations, oligopoly, optimization, bidding I. INTRODUCTION A. OPERATION OF THE MICROGRID

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“…With the wide access of new energy power generation and the vigorous promotion of distributed energy storage, DC micro-grid has developed rapidly [1], among which DC/DC converter used to connect various micro-power sources and power grid is the key research direction in the field of power electronics [2]. Because of its characteristics of wide voltage output range, bidirectional energy flow, high power density and efficiency, electrical isolation, and easy to realize soft switching [3], Dual Active Bridge (DAB) converter as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Backflow Power Optimization of DAB Based on Asymmetric Duty Cycle and Internal Phase Shift Control

2023

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Dual active bridge (DAB) converter with single-phase-shifting (SPS) control would produce large backflow power when voltage regulation ratio deviates from 1 or under light load, an asymmetric duty cycle and internal phase shift (ADIPS) control was proposed which controls the transmission power by duty cycle and internal phase-shift ratio and the backflow power can be eliminated under light load therefore improves the efficiency of DAB converter. By establishing mathematical models of inductor current and transmission power, the working principle of the proposed control method was given as well as the cause of backflow power was analyzed. The constraints of zero backflow power and an optimization control method of zero backflow power under ADIPS control was presented. At last, an experimental prototype is used to obtain the validation results, simulation and experimental results verify the excellent performance of the proposed control strategy in eliminating the backflow power of DAB converter under light load.

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The Selection of Optimal Structure for Stand-Alone Micro-Grid Based on Modeling and Optimization of Distributed Generators

Cited by 21 publications

References 55 publications

Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources

Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources

Game Theory-Based Bidding Strategy in the Three-Level Optimal Operation of an Aggregated Microgrid in an Oligopoly Market

Backflow Power Optimization of DAB Based on Asymmetric Duty Cycle and Internal Phase Shift Control

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