A soft computing approach to projecting locational marginal price

Nwulu, Nnamdi; Fahrioğlu, Murat

doi:10.1007/s00521-012-0875-8

Cited by 28 publications

(6 citation statements)

References 16 publications

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“…[73][74][75]. This can also aid in optimising the locational marginal price (LMP) or nodal prices to generate more electricity from the renewable energy [76]. According to the authors of [76] and [19], the intellectual capital of artificial neural networks and support vector machines can be deployed in increasing the penetration of renewable energy through economic parameter of nodal prices.…”

Section: Cluster 5: Human Capital Development and The Economymentioning

confidence: 99%

Analysing the Impact of Human Capital on Renewable Energy Penetration: A Bibliometric Reviews

2022

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In contributing to reducing the adverse effects of non-renewable energy sources, this paper researched how human capital can enhance the penetration level of renewable energy, which is highly abundant in Nigeria, Sub-Saharan Africa. This paper, using qualitative research methodology through Bibliometric analysis, reviewed three hundred and three (303) papers published between the year 2000 and March 2022. The bibliometric study covered publications per author, publications per country, research focus based on co-occurrence keywords, and research thread. The findings revealed that publications on how human capital can aid renewable energy penetration have been slow and in an infant stage in the past two decades. It also shows that there have been eighteen (18) papers on the subject papers in the last twenty years, showing the low level of human capital development in the energy sector. The intellectual patterns via the co-occurrence of keywords shows five (5) clusters, which are economics of renewable energy sources, human capital factors in environmental management, economic factors in energy supply and demand, sustainable energy factors, and human capital development and economy. These cluster areas revealed how human capital could be developed to increase the penetration level of the abundant renewable energy in the world. Thus, this paper recommends intensive efforts in optimizing human capital through inter-organizational collaboration on renewable energy technologies and periodic training.

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Section: Cluster 5: Human Capital Development and The Economymentioning

confidence: 99%

Analysing the Impact of Human Capital on Renewable Energy Penetration: A Bibliometric Reviews

2022

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“…If P r t is the amount of power transaction MG and main grid at a time t; locational marginal prices are used (given as γ t ) (Nwulu and Fahrioglu, 2013) for purchasing power between main and MG. Therefore, the cost of power transactions (C r (P r t )) can be obtained as:…”

Section: Grid-connected Microgrid Modelmentioning

confidence: 99%

Developing an Artificial Hummingbird Algorithm for Probabilistic Energy Management of Microgrids Considering Demand Response

et al. 2022

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This study proposes an artificial hummingbird algorithm (AHA) for energy management (EM) for optimal operation of a microgrid (MG), including conventional sources and renewable energy sources (RES), with an incentive-based demand response (DR). Due to the stochastic nature of solar and wind output power and the uncertainty of prices and load, a probabilistic EM with hybrid AHA and point estimation method (PEM) is proposed to model this uncertainty by utilizing the normal and Weibull distribution functions. The PEM method is considered a good tool for handling stochastic EM problems. It achieves good results using the same procedures used with the deterministic problems while maintaining low computational efforts. The proposed AHA technique is employed to solve a deterministic incentive DR program, with the goal of reducing the overall cost, which includes the cost of conventional generator fuel and the cost of power transaction with the main grid while taking into account the load demand. Two different case studies are tested. The simulation results of the proposed AHA is compared with the results of well-known metaheuristic algorithms to demonstrate its efficacy. According to AHA’s results, a total reduction of energy consumption by 104 KWh for the first case study and 2677 MWh for the second case study is achieved while achieving the lowest overall operating cost. The results demonstrate that the AHA is adequate for tackling the EM problem. Then, to examine the effect of uncertainty on the MG state, a probabilistic EM problem is solved using AHA-PEM.

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“…In this work, it is assumed that there is a power transaction between the MG and the main grid; hence power can either be sold from the main grid or transferred to it. Let power transferred at any time between MG and main grid as 𝐏 𝐫 𝐭 , Locational Marginal Prices (LMP's) (given as 𝛄 𝐭 ) [14] are used for purchasing the power between MG and the main grid. Hence, the cost for power transaction (𝐂 𝐫 (𝐏 𝐫 𝐭 )) is expressed as in Eq.…”

Section: Grid-connected Microgridmentioning

confidence: 99%

Energy Management of Microgrid Considering Demand Response Using Honey Badger Optimizer

Alamir¹,

Kamel²,

Megahed³

et al. 2022

REPQJ

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Recently, Microgrids (MGs) have received great attention for solving power system problems, due to their low environmental effects and their economic benefits. This paper proposes a new application of an effective metaheuristic optimization method, namely, Honey Badger Algorithm (HBA), to solve energy management for optimal dispatch of the gridconnected MG incorporating Demand Response programs (DRP). Honey badger algorithm is used to solve an incentive DRP, with the aim of minimizing the total cost, which includes conventional generators fuel cost and the cost of power transaction with the main grid considering the load demand. In this paper, two case studies are conducted using HBA and simulation results are compared with those obtained by other algorithms (particle swarm optimization and JAYA algorithm). First case consists of three diesel generators, a PV generator and a wind generator. To prove the scalability of the HBA, the second case, which is much larger, is tested. Simulation results for both case studies obtained by PSO, JAYA, and HBA are deeply discussed. The results show the HBA's effectiveness in solving the energy management with DR problem for MG compared with other well-known optimization techniques.

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A soft computing approach to projecting locational marginal price

Cited by 28 publications

References 16 publications

Analysing the Impact of Human Capital on Renewable Energy Penetration: A Bibliometric Reviews

Analysing the Impact of Human Capital on Renewable Energy Penetration: A Bibliometric Reviews

Developing an Artificial Hummingbird Algorithm for Probabilistic Energy Management of Microgrids Considering Demand Response

Energy Management of Microgrid Considering Demand Response Using Honey Badger Optimizer

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