Optimal design of hybrid renewable energy systems in buildings with low to high renewable energy ratio

Abstract

a b s t r a c tWe develop a simulation-based meta-heuristic approach that determines the optimal size of a hybrid renewable energy system for residential buildings. This multi-objective optimization problem requires the advancement of a dynamic multi-objective particle swarm optimization algorithm that maximizes the renewable energy ratio of buildings and minimizes total net present cost and CO 2 emission for required system changes. Three proven performance metrics evaluate the quality of the Pareto front generated by the proposed approach. The obtained results are compared against two reported multiobjective optimization algorithms in the related literature. Finally, an existing residential apartment located in a cold Canadian climate provides a test case to apply the proposed model and optimally size a hybrid renewable energy system. In this test application, the model investigates the potential use of a heat pump, a biomass boiler, wind turbines, solar heat collectors, photovoltaic panels, and a heat storage tank to produce renewable energy for the building. Furthermore, the utilization of plug-in electric vehicles for transportation reduces gasoline use where all power is generated by the building, and the utility provides the means to match intermittent renewable generation from solar and wind to the building electrical loads. Model results show that under the chosen meteorological conditions and building parameters a wind turbine, and plug-in electric vehicle technologies are consistently the optimal option to achieve a target renewable energy ratio. In particular, the optimization result shows that the renewable energy ratio can achieve near 100% by installing a 73 kW wind turbine, a 200 kW biomass boiler, and using plug-in electric vehicles. This option has a net present cost of C$705,180 and results in total CO 2 emission of 2.4 ton/year. Finally, a sensitivity analysis is performed to investigate the impact of economic constants on net present cost of the obtained non-dominated solutions.

Matching decentralized energy production and local consumption: A review of renewable energy systems with conversion and storage technologies

“…Second, in the model and optimization category, the most common optimization objectives are minimization of both cost and emissions in a multiobjective analysis. Conflicting objectives are demonstrated by a Pareto curve (Pelet et al, ; Sharafi & ELMekkawy, ; Sharafi, ElMekkawy, & Bibeau, ), while particle swarm optimization (García‐Triviño et al, ; Li et al, ; Safari, Ardehali, & Sirizi, ; Sharafi et al, ; Sharafi & ELMekkawy, ; Stoppato, Benato, Destro, & Mirandola, ), mixed‐integer linear programming optimization (Evins et al, ; Harb, Matthes, Wolisz, Streblow, & Müller, ; Majidi, Nojavan, Nourani Esfetanaj, Najafi‐Ghalelou, & Zare, ; Pantaleo, Giarola, Bauen, & Shah, ; Scheubel, Zipperle, & Tzscheutschler, ; Wouters et al, ; Wouters, Fraga, & James, ), fuzzy logic controller (Athari & Ardehali, ; Majidi et al, ; Safari et al, ), and evolutionary algorithm (Ahmadi et al, ; Pelet et al, ) appear as the main optimization methods in use. Some publications propose a novel approach for optimization or modeling/simulation of a system to better account for dynamic system complexities (Maleki, Pourfayaz, & Rosen, ; Pelet et al, ; Petruschke et al, ; Sharafi & ELMekkawy, ; Yang, Xiong, Qiu, Qiu, & Dong, ).…”

Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies

“…In this paper, the wind turbine type proposed is ENERCON E − 70, with a rated power capacity of 2300 Kw, some parameters of the ENERCON E − 70 wind turbine are listed in Table 1 [25][26][27].…”

Energy storage systems: power grid and energy market use cases

“…Smart buildings are also a popular and wide field for the testing of storage technologies. On the one hand, wide-ranging energy management systems (EMS -Energy Management System) are being developed and implemented for autonomous system [33] taking into account dynamic DMS [34] and optimal control strategies [35] also for hybrid [36] and PV-Wind combined supply [37] which utilize both stationary and mobile batteries as well as thermal storage systems to integrate RES optimally [38]. On the other hand, installations have been created, which facilitate systematic peak shaving in buildings [39], thus cutting the power input to buildings as well as connection costs.…”