scholarly journals A Method for Determining Customers’ Energy Shrinkage Cost

2020 ◽  
Vol 8 (3) ◽  
pp. 672
Author(s):  
CONNY KURNIAWAN WACHJOE ◽  
HERMAGASANTOS ZEIN ◽  
SITI SAODAH
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Allocation ◽  
Low Voltage ◽  
Equivalent Circuit Model ◽  
Power Losses ◽  
Network Efficiency ◽  
Loss Allocation ◽  
Cost Of Energy ◽  
The Cost

ABSTRAKPenyusutan energi adalah salah satu komponen biaya-biaya listrik yang harus dibayar oleh pelanggan-pelanggan pada tegangan sistem dari jaringan yang berbeda, jaringan tegangan tinggi, sedang dan rendah. Meskipun biaya bahan bakar campuran adalah sama untuk semua pelanggan, alokasi kerugian berbeda untuk setiap jaringan tersebut. Makalah ini mengusulkan suatu metode untuk menentukan alokasi biaya penyusutan energi untuk pelanggan-pelanggan dalam suatu model rangkaian ekivalen, dengan beban dikumpulkan pada setiap jaringan. Formulasi-formulasinya diturunkan untuk  mendapatkan alokasi kerugian yang adil di antara pelanggan-pelanggan berdasarkan hukum-hukum listrik. Hasil simulasi menunjukkan bahwa alokasi biaya penyusutan energi adalah 31%, 33% dan 36% untuk pelanggan tegangan tinggi, sedang dan rendah. Selain itu, efisiensi jaringan akan mempengaruhi total biaya penyusutan energi. Jika perhitungan kerugian daya menggunaka metode Aliran Daya Optimal, maka metoda ini dapat mengurangi kerugian sebesar ±3% atau setara dengan pengurangan biaya penyusutan energi sebesar 16%.Kata kunci: komponen biaya-biaya listrik, tegangan sistem, model rangkaian ekivalen, hukum-hukum listrik, alokasi biaya kerugian energi. ABSTRACTEnergy shrinkage is one component of electrical costs that must be paid by customers on the system voltage in different networks, high, medium, and low voltage networks. Although the fuel-mix costs are flat for all customers, loss allocation is different for each network. This paper proposes a method for determining the cost allocation of energy shrinkage to customers in an equivalent circuit model, with the loads collected for each network. Formulations are derived to get a fair allocation of losses among customers based on electric laws. The simulation results show that the cost allocation of energy shrinkage is 31%, 33%, and 36% for high, medium, and low voltage customers. Besides, network efficiency will affect the total cost of energy shrinkage. If power losses calculation uses the Optimal Power Flow method, it can reduce power losses by ±3% or equivalent to a reduction in the cost of energy shrinkage of 16%.Keywords: component of electrical costs, system voltage, eqivqlent sircuit model, electric laws, cost allocation of energy shrinkage

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

scholarly journals Comparison of Several Transmission Loss Allocation Procedures

2010 ◽  
Vol 44 (3) ◽  
pp. 289-296
Author(s):  
Mohammed Humayun Kabir
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transmission Loss ◽  
Detailed Comparison ◽  
Coefficient Matrix ◽  
Transmission Losses ◽  
Loss Allocation ◽  
Proportional Allocation ◽  
Transmission Loss Allocation

Transmission-loss is an inherent nature of power system. Determination of transmission losses for the purposes of billing in various interconnected trans-actions is an important issue to be solved exactly. Loss allocation is a procedure for subdividing the system transmission losses into fractions, the cost of which becomes the responsibility of network users. This paper focuses on transmission loss allocation procedures and provides a detailed comparison of some alternative algorithms: viz. 1) Incremental loss allocation, 2) A proportional allocation, 3) Preliminary loss allocation and 4) A direct methodology for loss allocation. A case study based on a 6-bus model power system has been provided. Finally conclusions and recommendations have been stated. Key words: Transmission loss allocation, DC optimal power flow, Deregulated power market, Loss coefficient matrix, Non-volatile procedure. DOI: 10.3329/bjsir.v44i3.4401 Bangladesh J. Sci. Ind. Res. 44(3),289-296, 2009

Optimal Transmission Switching Problem Utilizing an Enhanced Multi-Phase Seeker Optimization Algorithm

2016 ◽  
Vol 24 ◽  
pp. 85-102 ◽  
Author(s):  
Ragab A. El-Sehiemy ◽  
Mohammed Badeaa Shafiq ◽  
Ahmed M. Azmy
Keyword(s):  
Transmission Lines ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Savings ◽  
Production Costs ◽  
Voltage Deviation ◽  
Multi Phase ◽  
The Cost ◽  
Seeker Optimization Algorithm

This paper proposes a procedure based on a multi-phase seeker optimization algorithm (MSOA) for optimizing the commitment of transmission system. The under consideration problem is formulated with the aid of AC-based security constrained optimal power flow (SC-OPF) considering system constraints. The target is to detect transmission lines commitment schedule that reduces system production costs and enables sufficient reserve levels from both generation and transmission. The methodology is illustrated through several computational tests on IEEE 57 and IEEE 118 bus test systems to confirm the previous objectives. It is proven that numerical results based on the use the AC model demonstrate that the calculation time is short enough and the cost savings are reasonably better than DC power flow model. In addition, all transmission lines are preserved within their permissible boundaries and the voltage deviation is maintained at the least levels.

ANÁLISE COMPARATIVA DO CUSTO PARA APLICAÇÃO DE UMA LÂMINA DE IRRIGAÇÃO UTILIZANDO ENERGIA ELÉTRICA E DIESEL

2016 ◽  
Vol 31 (3) ◽  
pp. 259
Author(s):  
Arionaldo De Sá Júnior ◽  
Jacinto de Assunção Carvalho
Keyword(s):  
Low Voltage ◽  
Electric Energy ◽  
Electrical Energy ◽  
Minas Gerais ◽  
Linear Increase ◽  
Energy Company ◽  
Cost Of Energy ◽  
Irrigation Depth ◽  
Tariff Rates ◽  
The Cost

Objetivou-se com a realização deste trabalho, estimar o custo com energia elétrica e à diesel para aplicação de 1 milímetro de lâmina de irrigação em uma área de 1 hectare. O grupo tarifário considerado foi o “B” para baixa tensão e subgrupo “B2 - Rural”. Os valores tarifários aplicados foram obtidos na Companhia energética de Minas Gerais – CEMIG. O valor adotado para o diesel foi respectivo à média observada na região sul de Minas Gerais no segundo semestre de 2012. Para efeito de cálculos, os rendimentos globais do conjunto motobomba e alturas manométricas totais adotadas foram, respectivamente; 60%, 65%, 70%, 75% e 10, 25, 75, 100, 125, 150, 175 e 200 m.c.a. Para o cálculo do custo total com a aplicação da lâmina de 1mm ha-1 foi considerado que o custo com a energia na atividade de irrigação representa 65% e 75% para elétrica e diesel, respectivamente. Os resultados obtidos mostram um crescimento linear dos custos com energia com o aumento da altura manométrica total. A utilização de sistemas motobomba mais eficientes reduz o custo com energia elétrica na ordem de 7% a 20% e diesel entre 4% a 16%, para as situações propostas.Em todos os casos a energia elétrica é mais favorável com relação ao custo.Palavras-chave: Lâmina de irrigação, Motobomba, Tarifa, Grupo tarifário.COMPARATIVE ANALYSIS OF THE COST OF AN IRRIGATION DEPTH USING ELECTRIC ENERGY AND DIESELABSTRACT: The aim of this study was to estimate the cost of electricity and diesel use for application of 1 mm water depth in an area of 1 hectare. The tariff group considered was "B" for low voltage and subgroup "B2 - Rural". The applied tariff rates were obtained from the energy company of Minas Gerais - CEMIG. The value adopted for a liter of diesel fuel was the average observed in the southern region of Minas Gerais in the second semester  of 2012. To do the  calculation, the overall yields adopted for  the whole pump and manometer total elevation  were, respectively, 60%, 65%, 70%, 75% and 10, 25, 75, 100, 125, 150, 175, 200 meters of water column. To calculate the total cost of 1mm ha-1 application, it was considered that the cost of energy on irrigation activity represents 65% and 75% for electricity and diesel, respectively. The results showed a linear increase of energy costs by increasing the manometer total elevation. The use of more efficient pump systems reduces the cost of electric power in the range of 7% to 20% and of diesel by 4% to 16% considering the proposed situations. In all cases, the electrical energy is more advantageous regarding the cost.Keywords: Depth irrigation, Motor-pump, Tariff, Tariff Group.

scholarly journals Artificial Bee Colony Algorithm Based onK-Means Clustering for Multiobjective Optimal Power Flow Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Liling Sun ◽  
Jingtao Hu ◽  
Hanning Chen
Keyword(s):  
Information Exchange ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Test System ◽  
Population Diversity ◽  
Particle Swarm Optimizer ◽  
Nsga Ii ◽  
Bee Colony ◽  
Optimal Power ◽  
The Cost

An improved multiobjective ABC algorithm based onK-means clustering, called CMOABC, is proposed. To fasten the convergence rate of the canonical MOABC, the way of information communication in the employed bees’ phase is modified. For keeping the population diversity, the multiswarm technology based onK-means clustering is employed to decompose the population into many clusters. Due to each subcomponent evolving separately, after every specific iteration, the population will be reclustered to facilitate information exchange among different clusters. Application of the new CMOABC on several multiobjective benchmark functions shows a marked improvement in performance over the fast nondominated sorting genetic algorithm (NSGA-II), the multiobjective particle swarm optimizer (MOPSO), and the multiobjective ABC (MOABC). Finally, the CMOABC is applied to solve the real-world optimal power flow (OPF) problem that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results demonstrate that, compared to NSGA-II, MOPSO, and MOABC, the proposed CMOABC is superior for solving OPF problem, in terms of optimization accuracy.

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