A Generalized Framework for a Cost Optimization Scheme in a MicroGrid

Objectives: To develop a generalized formulation to determine the cost optimization scheme for a MicroGrid (MG) source by implementing Artificial Bee Colony algorithm. The generating resource with microgrid is a two-objective problem which consists of pv cell (solar cell) array, Wind Turbine (WT), Micro Turbine (MT), diesel generator and Fuel Cell (FC). Methods: The generating energy sources of the microgrid units are essential to minimize the operating cost of the output power which is generated. Here, the ABC algorithm is modelled into two stages. The optimum configuration of the microgrid at a minimum fuel cost is obtained by the first stage of the ABC algorithm. Findings: By using the minimum cost function, the second stage of the ABC algorithm was attained at the reduced operating and maintenance cost. The main aim is to minimization of fuel cost, fuel consumption cost and the emission such as NOX, SO2, and CO is reduced in these microgrid sources. Applications: For any required load demand the minimum fuel cost is obtained by using artificial bee colony algorithm.


Introduction
Microgrid is evolved because of the requirement for more extensible power systems, varying regulatory and various fiscal states, tradable of energy sources and environmental effect are gives lowers to the betterment of microgrid, which are adding main role in the power generation close to the time ahead. Here, the problem is handled by introducing multiple steps, starts with constructing the microgrid architecture model and the development of Artificial Bee Colony (ABC) algorithm. The Artificial Bee Colony algorithm is used to obtain the optimum usage of the microgrid generating energy resources and In ABC system model, irradiation, wind speed and temperature are the inputs. The algorithm proceeds to the next level of the other alternatives such as micro turbine, diesel engine fuel cell when the generating power from the photovoltaic panel and wind turbine is less than the customer demand. These are used depend on the total amount of load and the corresponding consumption of energy resources cost 1-2 .

Microgrid Topology
The name microgrid (µG) defined as the notion of small electrical power system related with a small scale power grid. It can operate independently or it can operate by combination of the other small power resources. One of the main aims of microgrid is to collective prosperities of nonconventional or conventional lower carbon generation services and high proficient combined heat and power systems. As shown in the Figure 1, the power generation in gross is equal to the power demand in gross.
The Figure 1, which shows that a micro grid system usually comprises of distribution generating resource, energy storage systems, distribution systems, and communicating devices and control systems.

System Modelling
dynamic regulation with fiscal outline, savings of energy and environmental impingement. The management of the MG units stand in need of precise economic model to report the operating as well as maintenance cost are taking into account.MG model is nonlinear and distinct in nature and to minimize the operating and maintenance costs, optimization tools are used here 3 .

Wind Turbine
Bellow model is used to estimate the wind turbine generator output. The start up speed is defined as the speed at which the rotor and blade impel to rotate. The lowest wind speed is referred as cut in speed at which the wind turbine will generate serviceable generated power. The wind turbines wind speed is between 7 to 10 mph. The wind turbine will generate electric power at least wind speed is called as rated wind speed. Normally, 25 to 35 mph is the range of wind speed for large machines. If the blade of the wind turbine starts rotating at the speed of 45 and 80 mph, then it's called as cut out speed. The cut-put speed is as the speed when its starts shutdown the wind speed at which turbine stops to rotate is called the cut-out speed/curling speed.
The output power generated by wind turbine generator:

Photovoltaic
The optimal Photovoltaic cell contains a separate diode associated with current source which is light generated one, Iph, here, its output current, I, can be expressed as: Where is cell saturated current, V T is voltage with thermal constraint kTc/q, where k is Boltzmann's constant = 1.38 10−23 J/K, Tc = cell temperature, q =charge of electron (1.6 · 10−19 C). The below model is used to surmise the generated output by the Photovoltaic cell.
where P -output power of the module at Irradiance P -Module max power at standard test condition

Diesel Generator
A diesel generator is the mixture of a diesel engine and an electric generator which generates electrical energy. This

Fuel Cell Cost
The static energy conversion device which gets electrical energy from chemical energy and also produces water as a product is defined as Fuel cells. The radio of the electrical power output and the fuel input is called as efficiency of fuel cell and it must be in the same units (Watt) 5 .
The fuel cost for the fuel cell is calculated as :

Micro Turbine
Micro turbines are mini combustion turbines nearly the size of a refrigerator within the range of 25 kW to 500 kW. They developed for truck turbocharger, supplementary power units of planes, and small jet engines 6 .
The fuel cost for the fuel cell is calculated as :

Battery Model
A battery is defined as a combination of multiple singular cells. A cell is the combination of materials and electrolyte starting with the simple chemical energy into electric energy. The chemical reaction takes place in the singular cell when it is discharged and reversed. Thus in the charged cell , electrical energy stored as chemical energy which can be recover as electrical energy when the cell is discharged. As energy storage device is very difficult to compress negative energy the supreme state of charge (SOCmax) is increased to 100% and state of charge (SOCmin) is decreased 20% of its amp hour capacity (AH), respectively 7 .

Proposed Method
The microgrid units can be chosen in such a way that it full fill the customer side load demands at lowest cost. The accurate economic model is required to manage the MG units. Here for producing the output power the operating case is also considered. The proposed method include Artificial Bee Colony (ABC) algorithm to minimizing the fuel consumption cost, maintenance costs, operating cost and emission cost .The major impartial function of MG is obtained based on the following necessities to lessening the operating costs in $/h of the microgrid: where P -generation with minimum limit, P -generation with maximum limit, Externality or spill over's cost is the profits or costs of a product or its manufacture that upset people exterior to the market for the product henceforth, the name is called externality Table 1. Here the aim is to reduce the maintenance cost and operating of MG, which is described as: Where, Here, the fuel consumption cost is represented as C j , the generating unit is measured in Rs/Litre for the diesel and Rs/kilo watt for the natural gas, the generating units of fuel consumption rate is represented as F i , the operating and maintenance cost represented as OM j , and i = type of emission used as a externality cost, EF ji is the generating unit emission factor; here the type of emission is represented as M, and the number of generating unit is represented as N 7 (Table 2).
The three groups of bees are considered in the ABC model viz: the employed bees, the onlooker's bees and the scout's bees. Here it assumes that each food source is assigned to each one of the artificial employed bee.A random initial population of food sources (NS) is generated as: , min, max, min, r and (0,1) ( ) Where, i=1,2,3,….,SN j=1,2,3,….,D The employed bees transfer the information about the food source to the onlookers. The onlookers tend to further looks for the food around the informed food source. Based on the probability value, the onlooker selects the food source (Table 3). The following process is involved in artificial bee colony algorithm, • Initially the food sources were generated for every employee bees. • Repeat the below process. • Every employed bee goes to food source, form a neighbour source around them and then assess its nectar amount and dances in the hive. This process is done in their memory. • Each onlooker lookouts the dance of the employed bees and selects one of their sources subject to the dances, and then goes to that corresponding sources. After selecting a neighbour around that, the bees assess its nectar amount. • Surplus food sources are replaced by a new food sources. These new food sources are found by scout's bee. • The optimal food source determined so far is recorded.
The above process is repeated until the requirements are met as shown in Figures 2-4.

Results
The proposed method is studied in the Matlab 7.10.0(R2014a) platform. The optimization problem contains a diversity of energy sources that are probable to be making in a microgrid. Here the minimization of fuel cost, operating and maintenance costs as well as emission cost were obtained by using artificial bee colony algorithm. Figure 5 shows the minimized cost of MG.

Conclusion
The optimum configuration of the microgrid at a minimum of fuel consumption cost and minimum of operating and maintenance cost can be attained for different microgrid units using proposed artificial bee colony method. It is clearly examined from the gained results that the ABC method has attained the best selection of the power generators of the MG under various power demands at a minimum cost. The proposed method is an effective technique to model and manage the MG connected system, which is more proficient compare to the other techniques. It can also be applied using Particle Swarm Optimization, Genetic Algorithm to obtain an efficient result.