MPC for Optimized Energy Exchange between Two Renewable-Energy Prosumers

Aldaouab, Ibrahim; Daniels, Malcolm; Ordóñez, Raúl

doi:10.3390/app9183709

Cited by 10 publications

(8 citation statements)

References 20 publications

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“…The MSGSDN architecture deals with several constraints: the preference of energy sources, the type of the building devices, the real time of equipment’s consumption and its security. As for Aldaouab, Daniels & Ordonez (2019) , they tried to optimize the energy exchange between two prosumers. Their optimisation problem is defined by a Model Predictive Control (MPC) framework based on future behaviour prediction algorithms.…”

Section: Related Workmentioning

confidence: 99%

A-RESS new dynamic and smart system for renewable energy sharing problem

Toumia

Hassine

2021

PeerJ Computer Science

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Energy is at the basis of any social or economic development. The fossil energy is the most used energy source in the world due to the cheap building cost of the power plants. In 2017, fossil fuels generated 64.5% of the world electricity. Since, on the one hand, these plants produce large amount of carbon dioxide which drives climate change, and on the other hand, the storage of existing world fossil resources is in continuous decrease, safer and highly available energy sources should be considered. Hence, for human well-being, and for a green environment, these fossil plants should be switched to cleaner ones. Renewable energy resources have begun to be used as alternatives. These resources have many advantages such as sustainability and environmental protection. Nevertheless, they require higher investment costs. In addition, the reliability of many planted systems is poor. In most cases these systems are not sufficient to ensure a continuous demand of energy for all in needy regions because most of their resources are climate dependent. The main contributions of this research are (i) to propose a natural formalisation of the renewable energy distribution problem, based on COP (Constraint Optimisation Problem), that takes into consideration all the constraints related to this problem; (ii) to propose a novel multi-agent dynamic (A-RESS for Agent based Renewable Energy Sharing System) to solve this problem. The proposed system was implemented and the obtained results show its efficiency and performance in terms of produced, consumed and lost energy.

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Section: Related Workmentioning

confidence: 99%

A-RESS new dynamic and smart system for renewable energy sharing problem

Toumia

Hassine

2021

PeerJ Computer Science

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“…Thus, the evolutionary game theory was used for a dynamic modelling of the buyers for selecting sellers. The particular approach from [29] consider a Model Productive Control (MPC) method, for transactions only between two SSRES (prosumers), to avoid selling the surplus electricity production to classical traders or suppliers. This work considers the direct transactions without P2P contracts and blockchain technologies.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition, the consumer-driven scenario is S5-minimum price for consumers. It should be mentioned that many papers are the same with the References [7,[11][12][13][14][15][16][17][18][20][21][22][23][25][26][27][28][29][30][31][32][33] presented in Table 1. Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A comparative state of the art between our method and the literature. [7,17] no no no no yes yes [11,12,25] yes no no no no yes [13] no no yes yes no yes [14,15] no no yes yes yes yes [16,23] yes no no yes no yes [18] no no yes no no no [20,26] no no yes no no yes [21,22,30] no no no no yes no [27] no no no yes yes no [28] no no yes no yes yes [29] no yes no no no yes [31] no yes no yes no no [32,33] no no no no yes yes Proposed approach yes yes yes yes yes yes A previous work of the authors, in [34], proposes only at principle level a particular approach for prosumers energy trading in µGs as an efficient P2P exchange based on the blockchain technology. Specifically, the algorithm solves a mathematical model for the latest challenges regarding both the ADN and the newest type of electricity market participants (prosumers) using virtual or crypto price as the transaction currency.…”

Section: Literature Reviewmentioning

confidence: 99%

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A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

et al. 2020

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A growing number of households benefit from government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefit from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand, and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

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“…A deviation below the nominal value produces a negative sign and aid in minimization, which is a direct marker of optimal energy usage. In the proposed work, a single-objective function is formulated with the weighted average method as in Equation (12). As these variables are scaled to normalized values, the importance weights are constrained to unity as in Equation (13).…”

Section: Formulation Of Objective Functionmentioning

confidence: 99%

Optimal Tuning of Model Predictive Controller Weights Using Genetic Algorithm with Interactive Decision Tree for Industrial Cement Kiln Process

et al. 2019

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Energy intense nature of cement kiln demands optimal operation to minimize the energy requirement. Optimal control of cement kiln is achieved by proper tuning of the model predictive controller (MPC), which is addressed in this work. Genetic algorithm (GA) is used to determine the MPC weights that minimize the overall energy utilization with reduced tracking error. Single objective function has been formulated using importance weighted performance metrics like energy utilization and integral absolute error in tracking the desired response. Importance weights are determined in specific to the control scenarios using an interactive decision tree (IDT). It interacts with the operator to detect the weaker metrics and raises the importance level for further improvement. The algorithm terminates after attending all the metrics with the consent from the operator. Five control scenarios that predominantly occur in industrial cement kiln have been considered in this study. It includes tracking, measured, and unmeasured disturbance rejection of pulse and Gaussian type noises. The results illustrate the minimized energy operation with the use of the proposed single objective function as compared with the multi-objective function-based GA tuning procedure.

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MPC for Optimized Energy Exchange between Two Renewable-Energy Prosumers

Cited by 10 publications

References 20 publications

A-RESS new dynamic and smart system for renewable energy sharing problem

A-RESS new dynamic and smart system for renewable energy sharing problem

A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

Optimal Tuning of Model Predictive Controller Weights Using Genetic Algorithm with Interactive Decision Tree for Industrial Cement Kiln Process

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