Algorithm for Demand Response to Maximize the Penetration of Renewable Energy

Abstract

Buildings are becoming smarter through the deployment of intelligent and energy-efficient technologies that reduce energy consumption while making buildings easier to manage and operate. Demand for lighting systems, efficient heating, ventilation and air conditioning (HVAC), as well as other types of hardware such as controls and sub-meters, is growing rapidly that needs more attention in terms of the energy efficiency. Moreover, the energy management of micro-generation or poly-generation system has always been very complex. Keeping the balance between demand and production is a challenging task for researchers. This paper investigates a simple yet very effective and intelligent demand response algorithm to mitigate the intermittency problem, providing an uninterrupted power supply to the users. The developed algorithm is fully capable of balancing the consumption and the production by controlling the user predefined load patterns that is based on the state of charge (SOC) of the storage system. The algorithm is tested on a microgrid system that consists of different loads, six photovoltaic (PV) solar panels, a small wind turbine system, and a set of lead-acid battery banks. The experimental result shows the maximum use of renewable energy while reducing the peak demand, cost of end-users and low or no carbon emissions. To achieve a significant reduction in energy consumption as well as to keep the balance between production and demand, this algorithm can be implemented for the efficient use of intermittent renewable energy sources. INDEX TERMS Building automation system, demand response, demand side management, distributed energy system, intelligent building, renewable energy, zero energy building. NOMENCLATURE

Contract-Theoretic Demand Response Management in Smart Grid Systems

“…We consider an indicative residential smart grid system consisting of |N | = 10 prosumers, who generate g t n KWh amount of electricity per time slot t, uniformly distributed in the interval [0, 16] KWh and their electricity consumption is also uniformly distributed in the interval l t n ∈ [5,25] KWh. The initial storage capacity is b t=0 n = 0KW h, ∀n ∈ N , the announced price is p t = 0.23 (unless otherwise stated) and the probability of the prosumers' types P r t n follows a uniform distribution.…”

“…With the evolution of the smart grid systems and towards meeting the electricity demands, the utility companies exploit the renewable energy resources as an alternative solution, due to the lack of availability of fossil fuels [5]. Also, the consumers are encouraged to install small wind turbine power generation systems or rooftop solar photovoltaics to cover partially or completely their electricity needs.…”

Performance Analysis of APSO and Firefly Algorithm for Short Term Optimal Scheduling of Multi-Generation Hybrid Energy System

“…We can represent the characteristic distance by ζ which defines the attractiveness value to be equal to β o /e for (4) or β o /2 for (5). In most cases, the attractiveness is taken to be the decreasing function defined by (7).…”

“…The problem of the coordination of these energy resources also known as the Economic Dispatch (ED) problem in the context is of the special interest in the field of optimization theory. A number of deterministic as well as the swarm based intelligence techniques are being explored by the researchers over the past few years to find the optimal solution of this particular optimization problem [7], [8]. The two major conventional energy resources being used are the thermal energy source and the hydroelectric source each having its own possible generation constraints.…”

Investigation on Sizing of Voltage Source for a Battery Energy Storage System in Microgrid With Renewable Energy Sources

“…It is considered as the most viable and promising approach [13,14] which minimizes the active power oscillation and the settling time in smart grid power systems. The recent advancements in Lithium-ion battery technology also offer various benefits in smart grids like high power, longer life, and high charge and discharge efficiency [15][16][17]. In addition to a small size and low weight, Li-ion batteries can offer high energy density and storage efficiency [18], which makes them suitable for portable devices.…”