Integrated renewable–conventional generation expansion planning using multiobjective framework

Aghaei, Jamshid; Akbari, Mohammad-Amin; Roosta, Alireza; Gitizadeh, Mohsen; Niknam, Taher

doi:10.1049/iet-gtd.2011.0816

Cited by 73 publications

(53 citation statements)

References 22 publications

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“…There have also been changes in the lines due to the EEP optimization according to Table 9. The results indicate the installation of new lines between buses (15,34) and (30,35) as well as enhancements in the line across buses (21,22).…”

Section: Case Studymentioning

confidence: 90%

“…The techniques used are diverse but may be classified as classic optimization [10e13], heuristic methods [14,15], and intelligent systems [16e19]. The joint modeling of EEP has recently been a subject of interest, so that several researches have been conducted in order to investigate the concurrent planning of systems with various energy systems such as natural gas and electricity [20e23].…”

Section: Introductionmentioning

confidence: 99%

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Considering cost and reliability in electrical and thermal distribution networks reinforcement planning

Abbasi

Seifi

2015

Energy

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Section: Case Studymentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Considering cost and reliability in electrical and thermal distribution networks reinforcement planning

Abbasi

Seifi

2015

Energy

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“…Moreover, increasingly prominent global environment and energy issues make the development of renewable energy resources highly valued by governments of many countries alongside the reform of the power industry [2,3]. Considering renewable resource penetration, these highly random, intermittent, and non-dispatchable power resources make it more difficult to develop a proper EM modeling approach, which is a necessary tool for decision-making analysis, market simulation, relevant policy design analysis, etc.…”

Section: Introductionmentioning

confidence: 99%

Application of Gradient Descent Continuous Actor-Critic Algorithm for Bilateral Spot Electricity Market Modeling Considering Renewable Power Penetration

et al. 2017

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Abstract:The bilateral spot electricity market is very complicated because all generation units and demands must strategically bid in this market. Considering renewable resource penetration, the high variability and the non-dispatchable nature of these intermittent resources make it more difficult to model and simulate the dynamic bidding process and the equilibrium in the bilateral spot electricity market, which makes developing fast and reliable market modeling approaches a matter of urgency nowadays. In this paper, a Gradient Descent Continuous Actor-Critic algorithm is proposed for hour-ahead bilateral electricity market modeling in the presence of renewable resources because this algorithm can solve electricity market modeling problems with continuous state and action spaces without causing the "curse of dimensionality" and has low time complexity. In our simulation, the proposed approach is implemented on an IEEE 30-bus test system. The adequate performance of our proposed approach-such as reaching Nash Equilibrium results after enough iterations of training are tested and verified, and some conclusions about the relationship between increasing the renewable power output and participants' bidding strategy, locational marginal prices, and social welfare-is also evaluated. Moreover, the comparison of our proposed approach with the fuzzy Q-learning-based electricity market approach implemented in this paper confirms the superiority of our proposed approach in terms of participants' profits, social welfare, average locational marginal prices, etc.

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“…Planning of the network while there is only one form of energy has been studied thoroughly during past years, considering electricity, natural gas and district heating networks. These models have incorporated integer programming [5], linear programming [6], branchand-bound [7], branch-exchange [8], heuristic models [8,9] and meta-heuristic models such as tabu search [10], genetic algorithms [11,12] and evolutionary algorithm [13][14][15] to solve the expansion problem. Moreover, the integrated planning of different energy forms has been also developed and addressed in a number of publications [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Unified electrical and thermal energy expansion planning with considering network reconfiguration

Abbasi¹,

Seifi²

2015

IET Generation, Transmission & Distribution

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Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio-inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed-integer non-linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines. The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems. NomenclatureSymbol and description P Line ij, min minimum active power between ith and jth bus P Line ij expected value of active power between ith and jth bus P Line ij, max maximum active power between ith and jth bus V min minimum value of voltage magnitude V i amplitude of the voltage at the ith bus V max maximum value of voltage magnitude δ i angle of the voltage at the ith bus Y ij amplitude of admittance between the ith and jth buses θ ij angle of branch between the ith and jth buses N P number of power units N C number of combined heat and power (CHP) units N h number of heat units N L number of lines C Elec.

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Integrated renewable–conventional generation expansion planning using multiobjective framework

Cited by 73 publications

References 22 publications

Considering cost and reliability in electrical and thermal distribution networks reinforcement planning

Considering cost and reliability in electrical and thermal distribution networks reinforcement planning

Application of Gradient Descent Continuous Actor-Critic Algorithm for Bilateral Spot Electricity Market Modeling Considering Renewable Power Penetration

Unified electrical and thermal energy expansion planning with considering network reconfiguration

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