Game-Theoretic Coalition Formulation Strategy for Reducing Power Loss in Micro Grids

Abstract

In this chapter, we move away from the smart-grid demand-side management topic to another important one of micro grids. Even though a significant progress has been achieved in the development of the micro grids, the power loss minimization between the micro grids and also between the macro station and an individual micro grid is still receiving much attention. Niyato and Wang [1] considered an algorithm aimed to optimize the transmission strategy in order to minimize the total cost including the power loss. The power losses minimization in the energy distribution networks has conventionally been investigated using a single and deterministic demand level. A novel algorithm to overcome this problem was designed in [2]. The “cost-aware smart micro grid network design” in [3] allows economic power transactions within the smart grid with manageable power losses. Meliopoulos et al. [4] also discussed power loss minimization issues by proposing a coordinated control scheme at real-time with the inclusion of distributed generation resources (micro grids) with the existing grid. A novel load management solution to coordinate the charging of multiple PHEVs in a smart grid system was considered in [5] which also considered the power loss problem. An efficient optimal reconfiguration algorithm for power loss minimization was studied in [6]. Costabeber et al. [7] demonstrated that the power loss reduction is viable without central controllers by exploiting local measurement, communication, and control capability in the micro grids. Saad et al. [8] used cooperative game theory to formulate novel cooperative strategies between the micro grids of an energy distribution network aimed to reduce the power loss. Also, Costabeber et al. [9] and Tenti et al. [10] discussed cooperative operation of neighboring power processing units to reduce distribution losses. Corso et al. [11] addressed the daily schedule of distributed generators to minimize power loss in a micro grid connected to the main grid. A more detailed methodology to develop an autonomous micro grid for coping with power loss can be found in [12]. Also, a heuristic-based greedy algorithm was proposed in [13] to reduce the power loss. A review of technologies, methodologies, and operational approaches for improving the efficiency of power distribution systems like micro grids can be accessed in [14]. The “autonomous regional active network management system” project aimed to design a distribution network power loss management algorithm in [15]. The tie-set graph theory and its application to smart grid networks was introduced to minimize the power loss in [16]. Power loss of the energy distribution networks was also considered in [17–21].