جستجوی مقالات مرتبط با کلیدواژه "profit" در نشریات گروه "برق"

In this paper, the electric vehicle (EV) charging station scheduling process is designed to maximize the profit of EVs owners and the station operator in two steps. First, a complete model is proposed to formulate the problem of charging and discharging EVs at charging stations in one-day-ahead 24-hours. The purpose of the program is to increase the profits of EVs owners charging station operator. In this manner, the charging behaviour of EVs such as arrival time to the station, the initial charge, the departure time from the station and the amount of requested energy are known as inputs of the problem. In the second stage, uncertainty is considered. Monte Carlo and Genetic Algorithm have been used to model the uncertainties in the problem and optimization, respectively. The output of the first stage is the optimal hourly load of the station. Then in the second stage, the optimal location of the charging station is determined by the obtained optimal load on the standard distribution network. So that the losses and voltage deviation index are minimized and the voltage stability index is maximized.

In this paper a new algorithm for clearing of independent reactive power is presented. In the proposed algorithm both traditional objective function of reactive power and some new indices are optimised. The traditional objective function is minimizing the total cost of market and maximizing the profit of players. Some new indices such as Units Association Rate, Producer Unit Profit Rate, Profit Distributing Rate, Production Sharing  Rate and Risk of Work In Capacity Limits are introduced in this paper. These indices show the effectiveness of the proposed clearing strategy. The proposed algorithm is implemented on IEEE 24 bus test system.

In this paper, the effect of connecting the charging station of electric vehicles is investigated considering the optimal charging and discharging scheduling at the station. Accordingly, in the first section, the planning process of the station aimed at maximizing the mutual benefits. In the second part, uncertainty was noted in the program's presence at the station based on the production of different scenarios. The statistical simulation method has been used to model the uncertainties in the problem. Possible scenarios are selected from generated scenarios considering the diversity of vehicle presence plans, station’s load curves, market price, and network load levels. Therefore, the equivalent load is calculated. In the third section, the effect of station loading on the distribution network was investigated based on equivalent loads (extracted based on optimal planning of the first part). Comparison of the station loading effect is carried out for IEEE 33-bus network in the MATLAB based on the loss indexes (loss cost) and the voltage drop of the buses. The results indicate loss reduction due to optimal planning at the station and its application in appropriate buses.

Lack of national budgets, high capital cost of infrastructure projects in power transmission grid and associated risks are among serious complications for transmission system expansion. A fundamental solution to overcoming these difficulties is attracting private sector capital to finance these projects. However private sector participation requires a certain level of profitability and risk management. In this paper a framework for attracting merchant investment to finance power projects has been proposed which can be adapted in other energy infrastructure systems. In the proposed algorithm, maximizing merchant investment is formulated as an objective function in the process of transmission expansion planning problem .The objective functions and constraints such as minimizing the construction cost of transmission lines, minimizing congestion costs, maximizing absorbed private investment and investment risks are used for problem modeling. The scenario analysis is used for modeling uncertainties; the NSGA II algorithm is used to obtain pareto-optimal solutions and the fuzzy satisfying method is used to choose the best solution. Final results are shown on the IEEE 24Bus reliability test system. With the proposed method the system planner can be assured about maximized merchant investment and also the profitability and risk hedging could be guaranteed for private sector investors.