## 1 Introduction
Demand Response (DR) and Demand Side Management (DSM) are two actions utilised in order to achieve flexibility in demand and generation in the distribution level. In both cases, it is fundamental that the customer is actively involved in load management, whereas it is considered that both industrial and residential consumers can contribute in the realisation of the fully operating smart grid. The meaning and the differences between the two concepts of DR and DSM is explained as follows [18]:  
* Demand Response is considered to be a bottom-up approach: the customer is provided with incentives so as to become active in load management and to shift/curtail loads. Such incentives can be convenient tariff schemes or economic benefits in general. In any case, the customer is responsible for managing his/her consumption. * Demand Side Management is considered a top-down approach: the energy provider/energy service company/aggregator is responsible for reducing or removing peak loads. Such an actor decides on measures to be implemented so as to increase the grid's stability by shifting or curtailing loads. DR has also been the argument of several international projects realised in Europe. For instance, in the Scalable Energy Management Infrastructure for Aggregation of Households (SEMIAH) project they implement a system for DR services based on aggregation and scheduling of electricity loads in households [19]. In the Peer-to-peer Smart Test (P2P SmarTest) project, special focus is given to market issues and the market models/competition relationships between different actors. It is suggested how to define the baseline methodology, how to design demand response products, the measurement and validation activities, the bidding process for implementing demand response and how to remove potential barriers in the system [20]. DR/DSM is a topic which attracts considerable scientific interest, with numerous articles in the literature addressing such issues. In reference [21] the distributed demand response (DDR) problem has been examined, where real-time balance in a neighbourhood has been studied. In reference [22], a distributed mechanism for demand response aggregation has been proposed. The mechanism is used for charging purposes and uses the day-ahead allocation and the customers' real consumption. Communication aspects in DR have been examined in reference [23], where residential customers are encouraged to participate in a DR program, even without the employment of a smart meter. In reference [24], the authors suggest a system for DSM, using the strategies of load shifting, flexible load shape, peak clipping, among others. DSM is also the focus of reference [25], where an electric vehicle charging schedule is proposed. The usage of a microcontroller associated with wireless telecommunication technologies is examined for the implementation of DSM in reference [26]. Market issues for DSM are examined in reference [27] with internal pricing being used for regulation service provisioning. Price responsive controllable loads is the topic of research in reference [28], highlighting the importance of customer involvement in DSM/DR programs. In reference [29], a distributed demand side energy management system is used, where an energy consumption scheduling game is used. The schedule of residential loads of each user is actually his/her strategies used. In reference [30] a specific DR program has been examined in terms of standards in DR communication. They aimed at increasing interoperability with respect to a DR communication standard. The OpenADR has been also examined and it has been found that the program had gaps regarding OpenADR. The whole work aimed at improving interoperability aspects of DR programs. In reference [31] a DSM test case has been applied on an end-to-end system, from the consumer to the energy provider.