Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices

Abstract

Daily increasing use of tidal power generation proves its outstanding features as a renewable source. Due to environmental concerns, tidal current energy which has no greenhouse emission attracted researchers' attention in the last decade. Additionally, the significant potential of tidal technologies to economically benefit the utility in long-term periods is substantial. Tidal energy can be highly forecasted based on short-time given data and hence it will be a reliable renewable resource which can be fitted into power systems. In this paper, investigations of effects of a practical stream tidal turbine in Lake Saroma in the eastern area of Hokkaido, Japan, allocated in a real microgrid (MG), is considered in order to solve an environmental/economic bi-objective optimization problem. For this purpose, an intelligent evolutionary multi-objective modified bird mating optimizer (MMOBMO) algorithm is proposed. Additionally, a detailed economic model of storage device is considered in the problem. Results show the efficiency of the suggested algorithm in satisfying economic/environmental objectives. The effectiveness of the proposed approach is validated by making comparison with original BMO and PSO on a practical MG.

Multi-Objective Optimal Scheduling Method for a Grid-Connected Redundant Residential Microgrid

“…The operative temperature is influenced mainly by the solar radiation load, heating/cooling demand, and the thermal runaway resulting from the difference between the indoor temperature and outdoor temperature. Accordingly, in this paper, equivalent thermodynamic parameter (ETP) models for the RFHCS and CHCS are established, respectively, to describe their mathematical relationships based on [16], as shown in Figure 2. demand, and the thermal runaway resulting from the difference between the indoor temperature and outdoor temperature.…”

“…demand, and the thermal runaway resulting from the difference between the indoor temperature and outdoor temperature. Accordingly, in this paper, equivalent thermodynamic parameter (ETP) models for the RFHCS and CHCS are established, respectively, to describe their mathematical relationships based on [16], as shown in Figure 2. In Figure 2, Q and Qs represent the heating/cooling demand (W) and solar radiation load (W), respectively; Tg, Tz, and Tout represent the radiant floor surface temperature (°C), the operative temperature (°C), and the outdoor temperature (°C), respectively, Cg, Cw, and CA represent the equivalent heat capacities (J/°C) of the radiant floor, the envelope structure, and the indoor air, respectively; RW represents the equivalent heat resistance (°C/W) for the envelope structure, while RZ represents the equivalent heat resistance (°C/W) of convection and radiation from the radiant floor surface to the indoor air and envelope structure.…”

Energy Management of a Hybrid Tidal Turbine‐Hydrogen Micro‐Grid: Losses Minimization Strategy

“…There are two main architectures of the EMS: the centralized and the decentralized systems . Many studies have presented the different EMS topologies of micro‐grids, that integrate tidal converters considering different optimization algorithms: genetic algorithm (GA), particle swarm optimization (PSO), the convex relaxation and the multi‐objective modified bird mating optimizer (MMOBMO). The different EMS strategies depend on formulating an objective function of minimizing the operational costs and the environmental impact (CO 2 emissions) of the micro‐grid integrating conventional generating units (e.g., Diesel generators) with respecting the different units constrains which provide the safe, the secure and the technically feasible operation.…”

Smart grid and energy district mutual interactions with demand response programs

“…1, pp. [1][2][3][4][5][6][7][8] This is an open access article published by the IET and Tianjin University under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) and subscribers (consumers). Javaid et al [15] developed a hybrid optimisation technique for power scheduling of smart homes based on DaH, RTP, and critical peak pricing schemes.…”