International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 5 Issue: 10 141 – 152 _______________________________________________________________________________________________ 142 IJRITCC | October 2017, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Novel Energy Management System for a DC MicroGrid Ashan Imantha Bandara 1 , Prabath Binduhewa 2 , Lilantha Samaranayake 3 , Janaka Ekanayake 4 Dept. of Electrical Eng. University of Peradeniya Peradeniya, Sri Lanka e-mail: 1. ashanimhb31@gmail.com; 2. prabath@ee.pdn.ac.lk; 3. lilantha@ee.pdn.ac.lk; 4. jbe@ee.pdn.ac.lk Abstract—This paper presents a design and simulation of a rule based energy management system for a dc MicroGrid that considers a cost function to reflect the battery degradation and that relates to the actual battery parameters.The derivation of the battery cost function and the utilization of that to ensure an optimum utilization of the battery energy storage were presented. The detailed description of the algorithms used to implement the EMS was presented. Simulation on PSCAD/EMTDC software was used to demonstrate the operation of the EMS both under grid connected and islanded modes. Further, the inertia support provided by the super-capacitor to avoid the collapseof the dc link of the MicroGrid was demonstrated. Keywords - MicroGrid; EMS; battery; super-capacitor __________________________________________________*****_________________________________________________ I. INTRODUCTION The adverse effects to the environment caused by burning of fossil fuel and depletion of fossil fuel triggered to search for alternative electricity generation sources. As an alternative, renewable energy sources such as photovoltaics and wind are now emerged as main stream power generation sources. As the renewable energy resource is intermittent and variable, they have introduced challenges in terms of maintaining voltages, line flows and stability of utility networks. In order to overcome some of these challenges MicroGrids have been considered. A MicroGrid is a low-voltage power system, smaller in capacity, consisting local generation and local loads with ability to operate autonomously or grid connected modes [1]-[4]. Customer point of view, MicroGrid improves the reliability of power whereas from the utility point of view, MicroGrid enables to connect higher percentage of renewables without destabilizing the existing utility network. In order to facilitate the stable operation of a MicroGrid under autonomous mode, energy storage within the MicroGrid is essential. Even though early MicroGrids consist of ac feeders, only dc MicroGrids and hybrid MicroGrids are emerging [1]-[4]. There are two main reasons to attract interest for dc MicroGrids [1], [5]-[7]. Renewable energy sources such as PV and energy storage produce dc voltages. In order to integrate them to ac MicroGrid, a dc-dc-ac conversion stage is essential. Further, many loads such as ICT equipment, entertaining equipment, portable appliances, etc. operates on dc internally thus requiring ac-dc(-dc) conversion stages when connecting to the ac MicroGrid. A dc MicroGrid consists of number of microsources (<500 kW) such as PV systems, wind turbines, and fuel cells [8], [9]. These microsources integrated to the MicroGrid through single-stage power conversion stage (often dc-dc). The utility interconnection should allow bi-directional power flow thus requiring a bi-directional ac-dc converter. The dc MicroGrid also requires energy storage to overcome the transient in the system and to negate medium or long term demand-supply mismatches. Supercapacitors and flywheels are used to overcome the transients within the MicroGrid while battery storage is used for medium or long term demand supply matching [10]-[14]. Hierarchical control that incorporates tertiary, secondary and primary control stages are usually employed for a dc MicroGrid. Primary control, which refers to the droop-control, responds to the parameters set by the secondary control such that the voltage is maintained within the acceptable values. Secondary control ensures that the power shared by each source is in accordance with the values scheduled by the tertiary control. Tertiary control refers to the Energy Management System (EMS) that uses a rule-based system or an optimization routine based on cost or loss optimization to schedule different constituent parts of the MicroGrid. Different EMSs are discussed in the literature. In [15] an EMS for an ac MicroGrid is presented. Six operating modes were defined based on the grid voltage and frequency. A rule based EMS was used to select the most appropriate operating mode that schedules the utility power exchange, energy storage, and renewable energy sources. In [16] an EMS application fora dc MicroGrid established in an office building is presented. The power balance is used as the decision making variable and the carbon emission is optimized. In [17] an EMS based on a rule based decision making system is implemented for an isolated dc MicroGrid. An EMS with layered architecture is presented in [18]. The topmost layer is the human machine interface. The next layer, the prediction layer, used metadata to predict the load and source profiles. Then the energy management layer defines the schedules and the