scholarly journals Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1462
Author(s):  
Md Mamun Ur Rashid ◽  
Fabrizio Granelli ◽  
Md. Alamgir Hossain ◽  
Md. Shafiul Alam ◽  
Fahad Saleh Al-Ismail ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Clean Energy ◽  
Energy Allocation ◽  
Green Economy ◽  
Optimal Energy ◽  
Management Scheme ◽  
Optimal Energy Allocation ◽  
Residential Consumers

Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy sources (RESs), energy storage systems (ESS), and optimal energy allocation strategies are used to resolve these difficulties. In this paper, the development of a cluster-based energy management scheme for residential consumers of a smart grid community is proposed to reduce energy use and monetary cost. Normally, residential consumers deal with household appliances with various operating time slots depending on consumer preferences. A simulator is designed and developed using C++ software to resolve the residential consumer’s REM problem. The benefits of the RESs, ESS, and optimal energy allocation techniques are analyzed by taking in account three different scenarios. Extensive case studies are carried out to validate the effectiveness of the proposed cluster-based energy management scheme. It is demonstrated that the proposed method can save energy and costs up to 45% and 56% compared to the existing methods.

scholarly journals Development of Home Energy Management Scheme for a Smart Grid Community

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4288 ◽  
Author(s):  
Md Mamun Ur Rashid ◽  
Fabrizio Granelli ◽  
Md. Alamgir Hossain ◽  
Md. Shafiul Alam ◽  
Fahad Saleh Al-Ismail ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Operating Time ◽  
Power Sharing ◽  
Electricity Cost ◽  
Home Appliances ◽  
Optimal Power ◽  
Management Scheme ◽  
Home Energy Management

The steady increase in energy demand for residential consumers requires an efficient energy management scheme. Utility organizations encourage household applicants to engage in residential energy management (REM) system. The utility’s primary goal is to reduce system peak load demand while consumer intends to reduce electricity bills. The benefits of REM can be enhanced with renewable energy sources (RESs), backup battery storage system (BBSS), and optimal power-sharing strategies. This paper aims to reduce energy usages and monetary cost for smart grid communities with an efficient home energy management scheme (HEMS). Normally, the residential consumer deals with numerous smart home appliances that have various operating time priorities depending on consumer preferences. In this paper, a cost-efficient power-sharing technique is developed which works based on priorities of appliances’ operating time. The home appliances are sorted on priority basis and the BBSS are charged and discharged based on the energy availability within the smart grid communities and real time energy pricing. The benefits of optimal power-sharing techniques with the RESs and BBSS are analyzed by taking three different scenarios which are simulated by C++ software package. Extensive case studies are carried out to validate the effectiveness of the proposed energy management scheme. It is demonstrated that the proposed method can save energy and reduce electricity cost up to 35% and 45% compared to the existing methods.

scholarly journals Optimal Energy Management of a Grid-Tied Solar PV-Battery Microgrid: A Reinforcement Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2700
Author(s):  
Grace Muriithi ◽  
Sunetra Chowdhury
Keyword(s):  
Renewable Energy ◽  
Reinforcement Learning ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Critical Role ◽  
Winter Season ◽  
Learning Approach ◽  
Solar Pv ◽  
Optimal Energy ◽  
Optimal Energy Management

In the near future, microgrids will become more prevalent as they play a critical role in integrating distributed renewable energy resources into the main grid. Nevertheless, renewable energy sources, such as solar and wind energy can be extremely volatile as they are weather dependent. These resources coupled with demand can lead to random variations on both the generation and load sides, thus complicating optimal energy management. In this article, a reinforcement learning approach has been proposed to deal with this non-stationary scenario, in which the energy management system (EMS) is modelled as a Markov decision process (MDP). A novel modification of the control problem has been presented that improves the use of energy stored in the battery such that the dynamic demand is not subjected to future high grid tariffs. A comprehensive reward function has also been developed which decreases infeasible action explorations thus improving the performance of the data-driven technique. A Q-learning algorithm is then proposed to minimize the operational cost of the microgrid under unknown future information. To assess the performance of the proposed EMS, a comparison study between a trading EMS model and a non-trading case is performed using a typical commercial load curve and PV profile over a 24-h horizon. Numerical simulation results indicate that the agent learns to select an optimized energy schedule that minimizes energy cost (cost of power purchased from the utility and battery wear cost) in all the studied cases. However, comparing the non-trading EMS to the trading EMS model operational costs, the latter one was found to decrease costs by 4.033% in summer season and 2.199% in winter season.

Optimal Energy Management for a Smart Grid using Resource-Aware Utility Maximization

2016 ◽  
Vol 17 (3) ◽  
pp. 251-266
Author(s):  
Brook W. Abegaz ◽  
Satish M. Mahajan ◽  
Ebisa O. Negeri
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Resource Utilization ◽  
Utility Maximization ◽  
Energy Resource ◽  
Optimal Energy ◽  
Central Controller ◽  
Optimal Energy Management ◽  
Energy Community ◽  
Resource Aware

Abstract Heterogeneous energy prosumers are aggregated to form a smart grid based energy community managed by a central controller which could maximize their collective energy resource utilization. Using the central controller and distributed energy management systems, various mechanisms that harness the power profile of the energy community are developed for optimal, multi-objective energy management. The proposed mechanisms include resource-aware, multi-variable energy utility maximization objectives, namely: (1) maximizing the net green energy utilization, (2) maximizing the prosumers’ level of comfortable, high quality power usage, and (3) maximizing the economic dispatch of energy storage units that minimize the net energy cost of the energy community. Moreover, an optimal energy management solution that combines the three objectives has been implemented by developing novel techniques of optimally flexible (un)certainty projection and appliance based pricing decomposition in an IBM ILOG CPLEX studio. A real-world, per-minute data from an energy community consisting of forty prosumers in Amsterdam, Netherlands is used. Results show that each of the proposed mechanisms yields significant increases in the aggregate energy resource utilization and welfare of prosumers as compared to traditional peak-power reduction methods. Furthermore, the multi-objective, resource-aware utility maximization approach leads to an optimal energy equilibrium and provides a sustainable energy management solution as verified by the Lagrangian method. The proposed resource-aware mechanisms could directly benefit emerging energy communities in the world to attain their energy resource utilization targets.

scholarly journals A Critical Assessment of Demand Response Programs Applied for Optimal Energy Management in Microgrids

2019 ◽  
Vol 8 (2S7) ◽  
pp. 344-349
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Power Flow ◽  
Renewable Energy Sources ◽  
Weather Condition ◽  
Optimal Energy ◽  
Autonomous Mode ◽  
Optimal Energy Management ◽  
Demand Response Programs ◽  
Microgrid Energy Management

Microgrid Energy Management is done to optimize microgrid performance. Power from Wind Turbines (WT) and Photo Voltaic (PV) modules into a microgrid addresses both factors of environmental concerns as well as sustainable energy production. Point of coupling with utility main grid is disconnected when microgrid functions in autonomous mode and it enhances steady microgrid operation when traditional grids face blackouts. Clean and renewable energy sources being easily affected by variation in weather condition, so taking into account of this uncertainty is essential while formulating power flow problem which can be done through demand response programs. This paper aims to investigate results obtained from research of several researchers scrutinizingly and analyzed critically for optimal energy management in microgrids using demand response programs. This paper also highlights the worthy findings of possible areas of research that would enhance the use of demand side management through demand response programs in microgrids.

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