**6.1 Energy management**

Energy management system (EMS) is an integration of all the algorithms procedures and devices to control and reduce the usage and the cost of energy used to deliver the load with its specifications. In a critical review [35] it has been pointed out that, most of the EMS for RES is concerned with flow and control of power and efficient battery utilization for its durability. But, a full-fledged control approach is yet to be developed.

Wu et al. [36] proposed optimal scheduling of the PV system for saving the timeof-use (TOU) cost. Sichilalu et al. [37] focused on a net-zero-energy building by demand side management. The energy management of a grid-connected WPVHPS has been introduced in hardware [38]. In this paper, the hardware, communication and how to meet its requests and functions are emphasized. The system could manage both grid-connected mode and stand-alone mode. EMS for both standalone and grid-connected hybrid RES are reviewed by Olatomiwa et al. [39]. EMS based on linear programming, intelligent techniques and Fuzzy logic controllers is discussed for various combinations. In the study [40] an EMS for controlling end-user building loads, AC, light, ice storage discharge, with adequate solar rooftop PV systems in groups to absorb PEV penetration using practical charging situations are developed without delaying EV charging. The EMS is developed in [41] for a micro-grid with RES that checks net excess generation, battery power and SOC and takes the decision whether to charge/discharge the battery, reduce PV generation, shed load or increase generation of PV by MPPT to control load end voltage. Boukettaya et al. [42] developed a supervisory control in a MG with WPVHPS, a flywheel energy storage system (FESS). Reihani et al. [43] studied the EMS for a MW-range battery energy storage system (BESS) with actual grid data serving for peak load shaving, power smoothing, and voltage regulation of a distribution transformer.

A distributed algorithm that extracts renewable energy sources on high priority through monitor and prediction of generation and loads online is proposed in [44]. It works to reduce cost and improve system stability. In [45] reports a battery management system (BMS) based on physics-based models of lithium-ion (Li-ion) batteries and vanadium redox-flow (VRF) BESS. In [46] a VRF storage device for frequency regulation and peak-shaving tasks is demonstrated. Multiple BMSs are required in order to reach the desired capacities at grid level demand. A part of the (EMS) in order to achieve specific operational objectives is described in [47].

Gelazanskas et al. [48] review demand-side management (DSM) and DR, including incentives, non-critical load scheduling and peak shaving methods.

Vasiljevska et al. [49] demonstrated an EMS in a medium voltage (MV) network with several MGs by a hierarchical multi-level decentralized arrangement. A power management system (PMS) is proposed for a PV-battery-based hybrid DC/AC MGs for both grid-connected and islanded modes [50]. It balances the power flows, regulates bus voltage automatically under different operating circumstances.
