Abstract
In order to ensure optimal and secure functionality of Micro Grid (MG), energy management system plays vital role in managing multiple electrical load and distributed energy technologies. With the evolution of Smart Grids (SG), energy generation system that includes renewable resources is introduced in MG. This work focuses on coordinated energy management of traditional and renewable resources. Users and MG with storage capacity is taken into account to perform energy management efficiently. First of all, two stage Stackelberg game is formulated. Every player in game theory tries to increase its payoff and also ensures user comfort and system reliability. In the next step, two forecasting techniques are proposed in order to forecast Photo Voltaic Cell (PVC) generation for announcing optimal prices. Furthermore, existence and uniqueness of Nash Equilibrium (NE) of energy management algorithm are also proved. In simulation, results clearly show that proposed game theoretic approach along with storage capacity optimization and forecasting techniques give benefit to both players, i.e., users and MG. The proposed technique Gray wolf optimized Auto Regressive Integrated Moving Average (GARIMA) gives 40% better result and Cuckoo Search Auto Regressive Integrated Moving Average (CARIMA) gives 30% better results as compared to existing techniques.
Highlights
Despite the ever increasing economic development attained by the world, many challenges are being faced in context of environmental inefficiency, environmental pollution, etc
In order to analyze game theory using proposed distributed algorithm, i.e., Distributed Energy Management (DEM), which represents the complete mechanism that how Micro Grid (MG) optimally decides price that has to be charged from users
GARIMA forecasting results turned out to be better as compared to Cuckoo Search Auto Regressive Integrated Moving Average (CARIMA) and other conventional techniques in MAPE
Summary
Despite the ever increasing economic development attained by the world, many challenges are being faced in context of environmental inefficiency, environmental pollution, etc. MG is considered as one of the reliable networks for establishing connection between renewable resources and consumers along with managing storage units [13] It can either be treated as controllable load or production system and can work in connection with grid. To achieve ideal economic performance by MG while ensuring reliability, various factors involve in energy Internet It includes conventional fossil fuel based dispatch able generators and renewable energy based distributed producers. The prior statistical knowledge of uncertain renewable resources energy production was considered to be precisely known and power trade among various market players is completely neglected This is the motivation behind proposed algorithm that performs distributed energy management along with integration of linear forecasting techniques, which makes proposed system more effective and reliable
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