A Distributed-Optimization-Based Architecture for Management of Interconnected Energy Hubs

Ferro, Giulio; Robba, Michela; Haider, Rabab; Annaswamy, Anuradha M.

doi:10.1109/tcns.2022.3165022

Cited by 9 publications

(3 citation statements)

References 42 publications

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“…In contrast to the above-mentioned papers, paper [130] presents a PAC approach, including elements that increase the algorithm convergence speed and enhance privacy in the exchange of primal and dual variables. Moreover, in a more recent paper [131], the authors propose a new distributed optimization algorithm, NST-PAC, is proposed ensuring the privacy of information exchange, with Nesterovs' acceleration-based iterations that lead to a fast solution.…”

Section: Ahrarinouri Et Al Inmentioning

confidence: 99%

Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management

et al. 2022

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In this paper, a survey is presented on the use of optimization models for the integration of electric vehicles (EVs) and charging stations (CSs) in the energy system, paying particular attention both to planning problems (i.e., those problems related to long term decisions such as the siting and sizing of CSs), and operational management problems (i.e., the optimal scheduling of EVs in smart grids, microgrids and buildings taking into account vehicle-to-grid (V2G) capabilities). Moreover, specific attention was dedicated to decision problems that couple transportation and electrical networks, such as the energy demand assessment for a vehicle over a path and routing and charging decision problems for goods and people transportation. Finally, an effort was dedicated to highlighting the integration and the use of EVs in very recent regulation frameworks, with specific reference to the participation in the balancing market through the figure of an aggregator and the inclusion in the management of Energy Communities (ECs) and sustainable districts.

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Section: Ahrarinouri Et Al Inmentioning

confidence: 99%

Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management

et al. 2022

Self Cite

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“…During the last decade, tremendous efforts have been performed on district heating systems, including combined heat and power (CHP) and distributed heat pumps, since they represent the most efficient solution to i) increase demand flexibility, ii) facilitate demand response, and iii) reduce the running cost of power grids [10]- [13]. Although they promote energy efficiency and grid stability, they do not make sense for every context.…”

Section: Introduction a Background And Motivationmentioning

confidence: 99%

A Stochastic Approach to Integrating Electrical Thermal Storage in Distributed Demand Response for Nordic Communities With Wind Power Generation

Dominguez¹,

Henao²,

Agbossou³

et al. 2023

IEEE Open J. Ind. Applicat.

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Demand response and distributed energy storage play a crucial role in improving the efficiency and reliability of electric grids. This paper describes a strategy for optimally integrating distributed energy storage units within a forward market to address space heating demand under a Stackelberg game in isolated microgrids. The proposed strategy performs distributed management in an offline fashion through proximal decomposition methods. It leverages stochastic programming to consider user flexibility degree and wind power generation uncertainties. Also, flexibility for demand response is realized through electric thermal storage (ETS). The performance of the proposed strategy is evaluated via simulation studies carried out through a case study in Kuujjuaq. Ten residential agents compose the demand side, each with flexibility levels and economic preferences. Economic benefits are evaluated on both sides across different ETS acceptance levels. The simulation results demonstrate significant benefits for the coordinator and customers. The proposed strategy reveals that ETS, in the presence of dynamic tariffs, reduces diesel consumption, maximizes renewable production and reduces grid stress.

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“…In comparison to analytical based optimization algorithms, a metaheuristic algorithm is free from derivation action to find optimal solution. Thus, a real time problem can be solved by any metaheuristic algorithm where it needs only the information of input and output of the system 9 . Therefore, researchers are giving priority to develop metaheuristic algorithms using natural concepts such as the concept of evolution, the behaviour of natural creatures and hunting procedure followed by animals, and so on [9][10][11] .…”

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confidence: 99%

A novel Human Conception Optimizer for solving optimization problems

Acharya

Das

2022

Sci Rep

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Computational techniques are widely used to solve complex optimization problems in different fields such as engineering, finance, biology, and so on. In this paper, the Human Conception Optimizer (HCO) is proposed as a novel metaheuristic algorithm to solve any optimization problems. The idea of this algorithm is based on some biological principles of the human conception process, such as the selective nature of cervical gel in the female reproductive system to allow only healthy sperm cells into the cervix, the guidance nature of mucus gel to help sperm track a genital tracking path towards the egg in the Fallopian tube, the asymmetric nature of flagellar movement which allows sperm cells to move in the reproductive system, the sperm hyperactivation process to make them able to fertilize an egg. Thus, the strategies pursued by the sperm in searching for the egg in the Fallopian tube are modeled mathematically. The best sperm which will meet the position of the egg will be the solution of the algorithm. The performance of the proposed HCO algorithm is examined with a set of basic benchmark test functions called IEEE CEC-2005 and IEEE CEC-2020. A comparative study is also performed between the HCO algorithm and other available algorithms. The significance of the results is verified with statistical test methods. To validate the proposed HCO algorithm, two real-world engineering optimization problems are examined. For this purpose, a complex 14 over-current relay based IEEE 8 bus distribution system is considered. With the proposed algorithm, an improvement of 50% to 60% in total relay operating times is observed comparing with some existing results for the same system. Another engineering problem of designing an optimal proportional integral derivative (PID) controller for a blower driven patient hose mechanical ventilator (MV) is examined. A significant improvement in terms of response time, settling time is observed in the MV system by comparing with existing results.

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A Distributed-Optimization-Based Architecture for Management of Interconnected Energy Hubs

Cited by 9 publications

References 42 publications

Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management

Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management

A Stochastic Approach to Integrating Electrical Thermal Storage in Distributed Demand Response for Nordic Communities With Wind Power Generation

A novel Human Conception Optimizer for solving optimization problems

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