Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods

Theo, Wai Lip; Lim, Jeng Shiun; Ho, Wai Shin; Hashim, Haslenda; Lee, Chew Tin

doi:10.1016/j.rser.2016.09.063

Cited by 225 publications

(105 citation statements)

References 309 publications

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“…Obviously, obtained equivalent capacities for the existing DG units are subtracted from the total capacity. The proposed mathematical model is given in Equation (14). The active and reactive power expressions are given in Equations (15) and (16), respectively.…”

Section: System Modelling and Methodologymentioning

confidence: 99%

“…The losses that occur during the transmission of the energy generated by large central power plants to the consumption areas can be reduced by generation at the distribution level where the consumption mainly takes place [7]. Besides, in the face of rising energy demands, the capacity of transmission In the literature, numerous studies can be found on DG planning [13][14][15][16]. These studies differ from each other in terms of their scope, the approach adopted and the methodology used in DG planning.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

“…The system is modelled in the Electrical Transient and Analysis Program (ETAP), which is software developed for power system analysis. (14). The active and reactive power expressions are given in Equations (15) and (16) …”

Section: Case Studymentioning

confidence: 99%

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Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

et al. 2018

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Abstract:Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number of such applications increases daily. As conventional power systems do not have an infrastructure that is compatible with these energy sources and generation systems, such integration applications may cause various problems in power systems. Therefore, planning is an essential part of DG integration, especially for power systems with intermittent renewable energy sources with the objective of minimizing problems and maximizing benefits. In this study, a mathematical model is proposed to calculate the maximum permissible DG integration capacity without causing overvoltage problems in the power systems. In the proposed mathematical model, both the minimum loading condition and maximum generation condition are taken into consideration. In order to prove the effectiveness and the consistency of the proposed mathematical model, it is applied to a test system with different case studies, and the results are compared with the results obtained from other models in the literature.

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Section: System Modelling and Methodologymentioning

confidence: 99%

Section: Motivation and Backgroundmentioning

confidence: 99%

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Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

et al. 2018

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“…Namely, the grid operators and aggregators use incentive-based while retailers tend to use more price-based strategies. Distributed generators have been significantly promoted in recent years through feed-in tariffs to make these resources more attractive to consumers [11][12][13]. Due to this initiative, the number of prosumers (consumers that own generation means) raised significantly in several countries (e.g., Portugal, Germany, UK).…”

Section: Introductionmentioning

confidence: 99%

Reschedule of Distributed Energy Resources by an Aggregator for Market Participation

2018

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Demand response aggregators have been developed and implemented all through the world with more seen in Europe and the United States. The participation of aggregators in energy markets improves the access of small-size resources to these, which enables successful business cases for demand-side flexibility. The present paper proposes aggregator's assessment of the integration of distributed energy resources in energy markets, which provides an optimized reschedule. An aggregation and remuneration model is proposed by using the k-means and group tariff, respectively. The main objective is to identify the available options for the aggregator to define tariff groups for the implementation of demand response. After the first schedule, the distributed energy resources are aggregated into a given number of groups. For each of the new groups, a new tariff is computed and the resources are again scheduled according to the new group tariff. In this way, the impact of implementing the new tariffs is analyzed in order to support a more sustained decision to be taken by the aggregator. A 180-bus network in the case study accommodates 90 consumers, 116 distributed generators, and one supplier.

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“…A detailed definition of optimal placement and production of DG units in a MG is still a topic of discussion [3][4][5][6][7][8], and studies are still ongoing as to what is the optimal operation of DGs.…”

Section: Introductionmentioning

confidence: 99%

A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm

Goodarzi

Kazemi

2017

Energies

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Microgrids are small scale power systems with local resources for generation; consumption and storage, that can operate connected to the main grid or islanded. For the islanding operation of microgrids, two important tasks are to share the load demand and maintain the voltage and frequency stabilities. In order to achieve this goal, a hierarchical control structure can be employed. This research presents a solution technique for finding the optimal site, production and droop coefficients of distributed generation (DG) units in microgrids. In this paper, three main factors are scrutinized through a multi-objective optimization approach. These factors include fuel consumption cost, stability and variations of voltage. To solve this optimization problem, an Imperialist Competitive Algorithm-Genetic Algorithm (ICA-GA) is presented. A fuzzy approach is used to search in non-dominated outcomes and to find the best answer. To show the effectiveness of the proposed method, it is implemented on 33-buses IEEE test systems. The simulation results exhibit the ability and efficiency of the proposed scheme to find the optimal solutions.

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Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods

Cited by 225 publications

References 309 publications

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

Reschedule of Distributed Energy Resources by an Aggregator for Market Participation

A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm

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