What objective function should be used for optimal auctions in the ISO/RTO electricity market?

This study proposes a method for optimally selecting the operating parameters of an energy storage system (ESS) for frequency regulation (FR) in an electric power system. First, the method allows the optimal objective function of the selected parameters to be set in a flexible manner according to the electric market environment. The objective functions are defined so that they could be used under a variety of electricity market conditions. Second, evaluation frequencies are created in order to simulate the overall lifespan of the FR-ESS. Third, calendar and cycle degradation models are applied to the battery degradation, and are incorporated into evaluations of the degradation progress during the entire FR-ESS lifespan to obtain more accurate results. A calendar life limit is set, and the limit is also considered in the objective function evaluations. Fourth, an optimal parameter calculation algorithm, which uses the branch-and-bound method, is proposed to calculate the optimal parameters. A case study analyzes the convergence of the proposed algorithm and the results of the algorithm under various conditions. The results confirmed that the proposed algorithm yields optimal parameters that are appropriate according to the objective function and lifespan conditions. We anticipate that the proposed FR-ESS algorithm will be beneficial in establishing optimal operating strategies.

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Optimal power flow with transmission cost solution under bilateral and multilateral transactions

Archives of Electrical Engineering ◽

10.2478/aee-2014-0018 ◽

2014 ◽

Vol 63 (2) ◽

pp. 227-245

Author(s):

Bastin Solai Nazaran J. ◽

K. Selvi

Keyword(s):

Objective Function ◽

Electricity Market ◽

Power Flow ◽

Optimal Power Flow ◽

Severity Index ◽

Test System ◽

Operating Conditions ◽

Real Power ◽

Transmission Cost ◽

Optimal Power

Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.

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UPFC Location and Performance Analysis in Deregulated Power Systems

Mathematical Problems in Engineering ◽

10.1155/2009/109501 ◽

2009 ◽

Vol 2009 ◽

pp. 1-20 ◽

Cited By ~ 6

Author(s):

Seyed Abbas Taher ◽

Ali Akbar Abrishami

Keyword(s):

Power Systems ◽

Objective Function ◽

Electricity Market ◽

Power Flow ◽

Reactive Power ◽

Unified Power Flow Controller ◽

Test Case ◽

Spot Prices ◽

Sensitivity Approach ◽

The Impact

We deal with the effect of Unified Power Flow Controller (UPFC) installation on the objective function of an electricity market. Also this paper proposes a Novel UPFC modelling in OPF which facilities the consideration of the impact of four factors on power market. These include the series transformer impedance addition, the shunt reactive power injection, the in-phase component of the series voltage and the quadrature component of the series voltage. The impact of each factor on the electricity market objective function is measured and then compared with the results from a sensitivity approach. The proposed sensitivity approach is fast so it does not need to repeat OPF solutions. The total impacts of the factors are used to offer UPFC insertion candidate points. It is shown that there is a clear match between the candidate points of the sensitivity method and those proposed by the introduced UPFC modelling in our test case. Furthermore, based on the proposed method, the relation between settings of UPFC series part and active and reactive power spot prices is presented.

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The Plant-Level Optimal Load Distribution Based on Economy and Environmental Protection

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.521.490 ◽

2014 ◽

Vol 521 ◽

pp. 490-493 ◽

Cited By ~ 1

Author(s):

Li Jun Qin ◽

Jia Di Li

Keyword(s):

Objective Function ◽

Electricity Market ◽

Load Distribution ◽

Power Plants ◽

Environment Protection ◽

Coal Consumption ◽

Optimal Load ◽

Mode Of Operation ◽

Plant Level ◽

Optimal Load Distribution

In order to meet new mode of operation in current Chinese electricity market, the paper puts forward the multi-objective optimization for plant-level load distribution based on economy and environment protection. It can balance the benefits between power plants and grids. While it can minimize coal consumption, reduce the emission of pollutants and make important effects on economy and environment. This paper proposes to calculate the sum cost of coal and sewage as the new model of objective function. Through the different weights on economy and environment, plants change the assigned load so as to make the objective function minimum and achieve the optimal load distribution. At the last we can get a optimal curve by simulation.

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Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources

Applied Sciences ◽

10.3390/app10082774 ◽

2020 ◽

Vol 10 (8) ◽

pp. 2774 ◽

Cited By ~ 5

Author(s):

Jamal Faraji ◽

Ahmadreza Abazari ◽

Masoud Babaei ◽

S. M. Muyeen ◽

Mohamed Benbouzid

Keyword(s):

Renewable Energy ◽

Objective Function ◽

Electricity Market ◽

Renewable Energy Sources ◽

Weather Prediction ◽

Mixed Integer ◽

Weather Data ◽

Specific Power ◽

Energy Sources ◽

Operation Cost

In recent years, taking advantage of renewable energy sources (RESs) has increased considerably due to their unique capabilities, such as a flexible nature and sustainable energy production. Prosumers, who are defined as proactive users of RESs and energy storage systems (ESSs), are deploying economic opportunities related to RESs in the electricity market. The prosumers are contracted to provide specific power for consumers in a neighborhood during daytime. This study presents optimal scheduling and operation of a prosumer owns RESs and two different types of ESSs, namely stationary battery (SB) and plugged-in electric vehicle (PHEV). Due to the intermittent nature of RESs and their dependency on weather conditions, this study introduces a weather prediction module in the energy management system (EMS) by the use of a feed-forward artificial neural network (FF-ANN). Linear regression results for predicted and real weather data have achieved 0.96, 0.988, and 0.230 for solar irradiance, temperature, and wind speed, respectively. Besides, this study considers the depreciation cost of ESSs in an objective function based on the depth of charge (DOD) reduction. To investigate the effectiveness of the proposed strategy, predicted output and the real power of RESs are deployed, and a mixed-integer linear programming (MILP) model is used to solve the presented day-ahead optimization problem. Based on the obtained results, the predicted output of RESs yields a desirable operation cost with a minor difference (US$0.031) compared to the operation cost of the system using real weather data, which shows the effectiveness of the proposed EMS in this study. Furthermore, optimum scheduling with regard to ESSs depreciation term has resulted in the reduction of operation cost of the prosumer and depreciation cost of ESS in the objective function has improved the daily operation cost of the prosumer by $0.8647.

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