Coalitional Game-Based Cost Optimization of Energy Portfolio in Smart Grid Communities

Chis, Adriana E.; Koivunen, Visa

doi:10.1109/tsg.2017.2784902

Cited by 103 publications

(66 citation statements)

References 22 publications

(66 reference statements)

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“…The benefit of such cooperation is shared among themselves. A known problem of DG is its intermittent supply of energy [28,68]. However, it was shown in [28] that with cooperation among renewable energy sources (RESs) and ESSs owners, the problem could be alleviated.…”

Section: Classification Based On Cooperative Game Theorymentioning

confidence: 99%

“…This includes deciding the appropriate structure to use for the trade, as well as the supporting control mechanisms to adopt. In this regards, one of the key questions is whether the trading structure should be distributed/P2P [24][25][26][27][28] or centralized through a platform/energy market [29][30][31][32] operation. Likewise, the form of control to be adopted to route information among the actors, whether distributed or central control, needs to be harmonized.…”

mentioning

confidence: 99%

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State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

et al. 2017

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Abstract:Transaction-based energy (TE) management and control has become an increasingly relevant topic, attracting considerable attention from industry and the research community alike. As a result, new techniques are emerging for its development and actualization. This paper presents a comprehensive review of TE involving peer-to-peer (P2P) energy trading and also covering the concept, enabling technologies, frameworks, active research efforts and the prospects of TE. The formulation of a common approach for TE management modelling is challenging given the diversity of circumstances of prosumers in terms of capacity, profiles and objectives. This has resulted in divergent opinions in the literature. The idea of this paper is therefore to explore these viewpoints and provide some perspectives on this burgeoning topic on P2P TE systems. This study identified that most of the techniques in the literature exclusively formulate energy trade problems as a game, an optimization problem or a variational inequality problem. It was also observed that none of the existing works has considered a unified messaging framework. This is a potential area for further investigation.

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Section: Classification Based On Cooperative Game Theorymentioning

confidence: 99%

mentioning

confidence: 99%

State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

et al. 2017

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“…This concept attempts to look at relationships among DER participants and predict optimal decisions. A novel coalitional game theory is proposed for minimizing electricity cost for RESs and ESSs by 18%, while load consumption is reduced by 3% [33]. The authors also considered energy exchange and penalty terms related to excess energy storage.…”

Section: Energy Management Using Deterministic and Chance-constrainedmentioning

confidence: 99%

“…The computational steps of the Jaya optimization technique depend upon the complexity at lines . The complexity of other lines (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) are superseded by these lines; the complexity of line 13 is influenced by line 15. Sub-lines 15-23 take O(1); while line 15 can iterate maximally with k iterations, and thus its cost is O(k).…”

Section: Jaya Algorithmmentioning

confidence: 99%

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Jaya based Optimization Method with High Dispatchable Distributed Generation for Residential Microgrid

et al. 2018

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This paper presents a model for optimal energy management under the time-of-use (ToU) and critical peak price (CPP) market in a microgrid. The microgrid consists of intermittent dispatchable distributed generators, energy storage systems, and multi-home load demands. The optimal energy management problem is a challenging task due to the inherent stochastic behavior of the renewable energy resources. In the past, medium-sized distributed energy resource generation was injected into the main grid with no feasible control mechanism to prevent the waste of power generated by a distributed energy resource which has no control mechanism, especially when the grid power limit is altered. Thus, a Jaya-based optimization method is proposed to shift dispatchable distributed generators within the ToU and CPP scheduling horizon. The proposed model coordinates the power supply of the microgrid components, and trades with the main grid to reduce its fuel costs, production costs, and also maximize the monetary profit from sales revenue. The proposed method is implemented on two microgrid operations: the standalone and grid-connected modes. The simulation results are compared with other optimization methods: enhanced differential evolution (EDE) and strawberry algorithm (SBA). Finally, simulation results show that the Jaya-based optimization method minimizes the fuel cost by up to 38.13%, production cost by up to 93.89%, and yields a monetary benefit of up to 72.78% from sales revenue.

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Optimal Allocation Method for a Fair Distribution of the Benefits in an Energy Community

et al. 2021

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Since their introduction in the EU RED II Directive in 2018, energy communities are a key topic for distributed photovoltaic systems. However, the distribution of the economic benefit among participants and the evaluation of the best composition of the energy community are still to be fully understood. Herein, a method for the optimal distribution of the benefit among participants based on their own contribution to the system is proposed. This method will be compared to other possible allocation methods and to achieve this, an energy community model which considers energy exchanges and economic expenditures is used. This model is a linear programming model based on a single‐objective optimization approach. The user economic contribution to the community can be quantified through sequential optimizations. The composition of energy communities affects the result of the optimization, as well as the contribution of each user: the total effective contribution of the participants is higher when the composition is more heterogeneous and the overall payoff in the analyzed case study increases by 12% passing from the lowest to the highest possible heterogeneity. In this latter scenario, users contribute differently as well, and their contribution is measured and ranges between 10% and 97%.

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Coalitional Game-Based Cost Optimization of Energy Portfolio in Smart Grid Communities

Cited by 103 publications

References 22 publications

State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

Jaya based Optimization Method with High Dispatchable Distributed Generation for Residential Microgrid

Optimal Allocation Method for a Fair Distribution of the Benefits in an Energy Community

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