Transmission Expansion Planning Considering Power Losses, Expansion of Substations and Uncertainty in Fuel Price Using Discrete Artificial Bee Colony Algorithm

Mahdavi, Meisam; Kimiyaghalam, A.; Alhelou, Hassan Haes; Javadi, Mohammad Sadegh; Ashouri, Ahmad; Catalão, João P.S.

doi:10.1109/access.2021.3116802

Cited by 33 publications

(16 citation statements)

References 26 publications

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Section: Smart Gridmentioning

confidence: 99%

“…Planning in distribution networks has been considered by the work of [61,62]. Mahdavi et al [61] work on expanding transmission lines utilizing the artificial bee colony algorithm to minimize cost of network expansion, power losses in load and generation. On the other hand, Maji and Acharjee [62] aim to determine the minimum number of Phase Measurement Units (PMUs) to make the distribution network observable.…”

Section: Smart Gridmentioning

confidence: 99%

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Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Syed

Sierra-Sosa

Kumar

et al. 2022

Sensors

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One of the prime aims of smart cities has been to optimally manage the available resources and systems that are used in the city. With an increase in urban population that is set to grow even faster in the future, smart city development has been the main goal for governments worldwide. In this regard, while the useage of Artificial Intelligence (AI) techniques covering the areas of Machine and Deep Learning have garnered much attention for Smart Cities, less attention has focused towards the use of combinatorial optimization schemes. To help with this, the current review presents a coverage of optimization methods and applications from a smart city perspective enabled by the Internet of Things (IoT). A mapping is provided for the most encountered applications of computational optimization within IoT smart cities for five popular optimization methods, ant colony optimization, genetic algorithm, particle swarm optimization, artificial bee colony optimization and differential evolution. For each application identified, the algorithms used, objectives considered, the nature of the formulation and constraints taken in to account have been specified and discussed. Lastly, the data setup used by each covered work is also mentioned and directions for future work have been identified. This review will help researchers by providing them a consolidated starting point for research in the domain of smart city application optimization.

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Section: Smart Gridmentioning

confidence: 99%

Section: Smart Gridmentioning

confidence: 99%

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Syed

Sierra-Sosa

Kumar

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…and NEP [45][46][47][48][49][50][51][52][53][54][55]. The authors of [2][3][4] pay considerable attention to the prediction of uncertainties and the efficiency of the obtained generation expansion plans in a DC power flow-based framework.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Simultaneous generation and network expansion planning in large‐scale power systems under exact AC power flow equations

Mahmoudi

Alizadeh

2022

IET Generation Trans & Dist

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This article presents a novel three-step structure for simultaneous generation and network expansion planning under the exact AC power flow equations. This tractable structure allows for detailed investment decisions on new generation and network facilities. In the first step of the proposed coordinated planning framework, a power system is partitioned into regions based on electrical and geographical distances. Network aggregation in the first step is achieved by a new linear clustering model ameliorating both computational efficiency and accuracy. In the second step, the aggregated power system with a specific number of regions is cost-effectively expanded on a regional basis considering inter-regional power flows. In the third step, new generation and network facilities imposed by the second step of the proposed coordinated planning framework are allocated in each region. Moreover, intra-regional systems are cost-effectively expanded by new transmission lines and transformers. The proposed approach is implemented on IEEE 30-bus, 39-bus, 300-bus, and 1,354-bus test systems. The simulation results illustrate its high advantages from accuracy, practicality, and tractability points of view.

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“…Although all proposals in the literature can be modified to consider the entire operating year [10,13] instead of representative days, the computational cost increases a lot due to the need to represent the power balance constraint considering the transmission network for the entire planning horizon [14] by using, for instance, linear programming or metaheuristics formulations [15]. To avoid this problem, in the present work, this representation of the transmission network is done in a distributed way through the Benders decomposition and parallel computation.…”

Section: Motivationmentioning

confidence: 99%

Block-Based Multicut Benders Decomposition Algorithm for Transmission and Energy Storage Co-Planning

Oliveira

Paula

Oliveira

et al. 2022

International Transactions on Electrical Energy Systems

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This study proposes a block-based multicut Benders decomposition algorithm to solve the co-planning of transmission expansion and energy storage problem in a bi-level approach. The proposal breaks the chronological representative period into multiple subperiods blocks. This division makes it possible to use parallel computation methods to solve each block simultaneously, reducing the simulation time, which allows the use of a more extensive time window to model the variability of random variables of the system, such as wind and load. In the proposed algorithm, the master problem defines the State of Charge (SoC) of the energy storage devices between the blocks and the investment in transmission and energy storage devices. To demonstrate the effectiveness of the proposed method, different sizes of representative periods are evaluated in three test systems: Garver 6-bus, IEEE-RTS 24-bus, and IEEE-118 188-bus. The tests compare the performance of the proposed block-based multicut Benders decomposition algorithm with the usual approach applied in the literature considering Benders decomposition and the complete problem formulated as a Mixed-Integer Linear Programming (MILP) problem.

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Transmission Expansion Planning Considering Power Losses, Expansion of Substations and Uncertainty in Fuel Price Using Discrete Artificial Bee Colony Algorithm

Cited by 33 publications

References 26 publications

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Simultaneous generation and network expansion planning in large‐scale power systems under exact AC power flow equations

Block-Based Multicut Benders Decomposition Algorithm for Transmission and Energy Storage Co-Planning

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