A Robust Model for Multiyear Distribution Network Reinforcement Planning Based on Information-Gap Decision Theory

Ahmadigorji, Masoud; Amjady, Nima; Dehghan, Shahab

doi:10.1109/tpwrs.2017.2732447

Cited by 51 publications

(27 citation statements)

References 32 publications

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“…The IGDT methodology is a non-probabilistic riskmanagement approach to determine a robust solution under different uncertainty sources [9], [10]. The information-gap models quantify the variation interval of the uncertain variable as the gap between what is known and what is unknown.…”

Section: Information-gap Decision Theorymentioning

confidence: 99%

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Optimal Energy Providing Strategy of Micro-Grid's Operator Based on a Game Theoretical Approach

Dehghan

Khojasteh

Marzband

et al. 2018

2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)

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Operators of micro-grid as privately-owned sectors try to optimally determine their energy supply strategy aiming at maximizing their profits. Smart grid infrastructures enable residential consumers to modify their electricity consumption in response to energy prices. Clearly, increasing energy tariffs have positive impacts on the operator's profit. Additionally, sensitivity of consumption to selling prices leads to demand reduction by increasing energy tariffs. Therefore, operators of micro-grids retain a tradeoff between energy tariffs and demand. This paper presents a game theoretical approach for operators of micro-grids to supply the required energy of price-sensitive clients. Additionally, the informationgap decision theory (IGDT) is used to handle the financial risk arising from the uncertain wholesale prices. Simulation results justify the performance of the proposed approach.

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Section: Information-gap Decision Theorymentioning

confidence: 99%

“…represent the total costs of purchasing electricity from the wholesale market, the forward contract, and the total operation cost of DGs at hour t, respectively. The procured power affect the wholesale procurement costs at hour t as given in(10):…”

mentioning

confidence: 99%

Optimal Energy Providing Strategy of Micro-Grid's Operator Based on a Game Theoretical Approach

Dehghan

Khojasteh

Marzband

et al. 2018

2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)

Self Cite

View full text Add to dashboard Cite

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“…In other words, IGDT determines the maximum uncertainty radius of the uncertain parameters by satisfying the objective function in the predefined interval. Notable efforts have been made in the area of studying uncertainty in electrical energy networks such as bidding strategies in the power systems [15], unit commitment [16] and restoration of electrical distribution systems [17], self-scheduling of generation companies [18]. Table I indicates the comparison of the main contributions of the literature and the proposed model in studying the integrated gas and electricity networks by providing summarized cases on the remarkable contribution of models.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

Mirzaei

Nazari-Heris

Mohammadi‐Ivatloo

et al. 2020

IEEE Systems Journal

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“…A stochastic methodology that maximizes the installed capacity of the renewable-based DG units while minimizing the energy losses and consumption of loads was proposed in [11]. An information-gap decision theory-based model that was proposed in [12] where the allocation of dispatchable DG units and circuit reinforcement were considered in an uncertain environment. Moreover, a short-term planning approach for conductor replacement of circuits, siting and sizing of wind-based DG units and CBs, and protection devices of EDSs was proposed in [13] where a genetic algorithm was used to find the solution of this problem.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Short-Term Planning of Electrical Distribution Systems Considering Siting and Sizing of Renewable Energy Based DG Units

Melgar‐Dominguez

Pourakbari‐Kasmaei

Mantovani

2019

IEEE Trans. Sustain. Energy

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Short-term planning is a decision-making process that aims at ensuring proper performance of electrical distribution systems (EDSs) within a short period of time. In recent years, this process has faced a significant challenge due to the integration of renewable energy based technologies. To handle such complicated planning problem most suitably, sophisticated algorithms are required. This paper proposes a mixed-integer linear programming model to find the optimal short-term plan of EDSs considering siting and sizing of capacitor banks and renewable energy sources, conductor replacement of overloaded circuits, and voltage regulators allocation. Besides considering the economic aspects, the environmental issues are also considered to promote a low carbon emission system. To address the uncertainties of electricity consumption and renewable energy output power, a two-stage robust optimization model is used, and to handle this model more efficiently, the column and constraint generation algorithm is applied. A 135-node distribution system is studied under different conditions to assess the performance of the proposed approach. Results show that the planning actions, for each case study, improve the efficiency of EDS and mitigate the pollutant emissions at the distribution level.

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A Robust Model for Multiyear Distribution Network Reinforcement Planning Based on Information-Gap Decision Theory

Cited by 51 publications

References 32 publications

Optimal Energy Providing Strategy of Micro-Grid's Operator Based on a Game Theoretical Approach

Optimal Energy Providing Strategy of Micro-Grid's Operator Based on a Game Theoretical Approach

A Novel Hybrid Framework for Co-Optimization of Power and Natural Gas Networks Integrated With Emerging Technologies

Adaptive Robust Short-Term Planning of Electrical Distribution Systems Considering Siting and Sizing of Renewable Energy Based DG Units

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