## 1 Introduction  
Global energy demands are increasing day by day and most of this demand is currently met using non-renewable sources. Traditional power systems are centralized and depend primarily on large scale power plants based on coal, nuclear, petroleum and natural gas etc. However, non-renewable energy sources are limited and produce Green House Gas (GHG) emissions which can eventually cause unpleasant and precarious climate changes [1, 2]. Therefore, most governments and researchers around the world are focusing on renewable energy sources such as solar, water, wind etc. Consumers are also being encouraged to produce energy from renewable sources and to store the excessive energy for future usage or to provide it back to the utility grid for the sake of financial benefit. These trends become clearer in the \"literature review\" section of this work. The business model of conventional grid depends on the interaction between distribution and transmission but the consumer is not actively involved. Dynamic requirements involving end users, such as Demand Side Management (DSM), lead to a more interactive system, namely smart grid [3; 4]. The smart grid is characterized with a bi-directional flow of energy and information and involves an advanced power system along with integrated communication infrastructure [5]. The smart grid concept aims at providing a sustainable, secure and economic power supply with the active involvement of consumers. Smart grid applications for energy management include Advanced Metering Infrastructure (AMI) and Home Energy Management System (HEMS). AMI is the communication infrastructure enabling two-way communications among utilities and users [6; 7], while HEMS is used to optimize home energy using different operations and algorithms [8]. AMI and HEMS are employed to manage the increasing demand efficiently. Information coming from the smart meters indicates how, when, and where consumers can manage their electricity usage [9; 10]. There are different methods for managing the peak demand including Demand Response (DR) programs offered by utilities according to the requirements of different periods of day. Demand Side Management (DSM) is the mechanism used to implement DR programs. DSM is an important tool used for load shifting to off-peak hours in order to fulfill the energy demand as well as minimize the energy cost. Shifting the load to off-peak hours results in a balanced power production curve. This in turn reduces the need for expensive and GHG emitting plants. One way of implementing DSM is by introducing price dependent time slots and reducing energy consumption in peak hours [8; 11]. DSM comprises of two major elements [12]:  
* Load shifting: Load shifting can be done using the DR program which can shift the load in peak hours to off peak hours on a long-term or short-term basis. * Energy efficiency and conservation: This is required in order to influence the consumers to reduce the energy usage for the sake of financial benefit. The advantages of DSM include reduction in utility bills, reduction in GHG emissions and cost saving by avoiding installation of new power plants. Note that DSM is a smart grid application aimed at energy conservation and load balancing. As we will see in later sections, prosumer-based energy management influences the users to generate more energy. This in turn helps in achieving the above mentioned DSM purposes. Renewable energy produced by consumers can be shared/sold to other consumers and the grid; this sharing of energy converts a consumer into prosumer [3]. Prosumers not only consume energy but also sell/share excessive energy generated by renewable energy sources with the grid and/or with other consumers in a community as shown in Figure 1. This phenomenon helps to address the environmental, social and economic concerns related to increasing energy demand.