Time-horizont distributed energy resources scheduling considering the integration of real-time pricing demand response

2015 ◽  
Author(s):  
M. Silva ◽  
H. Morais ◽  
T. Sousa ◽  
P. Faria ◽  
Z. Vale
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Real Time Pricing

Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response

2015 ◽  
Vol 138 ◽  
pp. 695-706 ◽  
Author(s):  
Qi Wang ◽  
Chunyu Zhang ◽  
Yi Ding ◽  
George Xydis ◽  
Jianhui Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Electricity Markets ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy

Energy management of a microgrid using demand response strategy including renewable uncertainties

2021 ◽  
Vol 22 (1) ◽  
pp. 85-100
Author(s):  
Suchitra Dayalan ◽  
Rajarajeswari Rathinam
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Demand Response ◽  
Effective Means ◽  
Operating Cost ◽  
Energy Resources ◽  
Response Strategy ◽  
Distributed Energy ◽  
Real Time Control ◽  
Minimum Operating

Abstract Microgrid is an effective means of integrating multiple energy sources of distributed energy to improve the economy, stability and security of the energy systems. A typical microgrid consists of Renewable Energy Source (RES), Controllable Thermal Units (CTU), Energy Storage System (ESS), interruptible and uninterruptible loads. From the perspective of the generation, the microgrid should be operated at the minimum operating cost, whereas from the perspective of demand, the energy cost imposed on the consumer should be minimum. The main key in controlling the relationship of microgrid with the utility grid is managing the demand. An Energy Management System (EMS) is required to have real time control over the demand and the Distributed Energy Resources (DER). Demand Side Management (DSM) assesses the actual demand in the microgrid to integrate different energy resources distributed within the grid. With these motivations towards the operation of a microgrid and also to achieve the objective of minimizing the total expected operating cost, the DER schedules are optimized for meeting the loads. Demand Response (DR) a part of DSM is integrated with MG islanded mode operation by using Time of Use (TOU) and Real Time Pricing (RTP) procedures. Both TOU and RTP are used for shifting the controllable loads. RES is used for generator side cost reduction and load shifting using DR performs the load side control by reducing the peak to average ratio. Four different cases with and without the PV, wind uncertainties and ESS are analyzed with Demand Response and Unitcommittment (DRUC) strategy. The Strawberry (SBY) algorithm is used for obtaining the minimum operating cost and to achieve better energy management of the Microgrid.

scholarly journals A Real-Time Monitoring Platform for Distributed Energy Resources in a Microgrid—Pilot Study in Oman

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1803
Author(s):  
Nasser Hosseinzadeh ◽  
Ahmed Al Maashri ◽  
Naser Tarhuni ◽  
Abdelsalam Elhaffar ◽  
Amer Al-Hinai
Keyword(s):  
Real Time ◽  
Communication Channel ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Small Scale ◽  
Area Network ◽  
Distributed Energy ◽  
Real Time Monitoring ◽  
Holistic View ◽  
Monitoring Platform

This article presents the development of a platform for real-time monitoring of multi-microgrids. A small-scale platform has been developed and implemented as a prototype, which takes data from various types of devices located at a distance from each other. The monitoring platform is interoperable, as it allows several protocols to coexist. While the developed prototype is tested on small-scale distributed energy resources (DERs), it is done in a way to extend the concept for monitoring several microgrids in real scales. Monitoring strategies were developed for DERs by making a customized two-way communication channel between the microgrids and the monitoring center using a long-range bridged wireless local area network (WLAN). In addition, an informative and easy-to-use software dashboard was developed. The dashboard shows real-time information and measurements from the DERs—providing the user with a holistic view of the status of the DERs. The proposed system is scalable, modular, facilitates the interoperability of various types of inverters, and communicates data over a secure communication channel. All these features along with its relatively low cost make the developed real-time monitoring platform very useful for online monitoring of smart microgrids.

A non-cooperative game based energy management considering distributed energy resources in price-based and incentive-based demand response program

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Monika Gaba ◽  
Saurabh Chanana
Keyword(s):  
Energy Management ◽  
Cooperative Game ◽  
Demand Response ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Energy Storage Devices ◽  
Electricity Cost ◽  
Distributed Approach ◽  
The Impact

Abstract Demand response (DR), an integral part of the smart grid, has great potential in handling the challenges of the existing power grid. The potential of different DR programs in the energy management of residential consumers (RCs) and the integration of distributed energy resources (DERs) is an important research topic. A novel distributed approach for energy management of RCs considering the competitive interactions among them is presented in this paper. The impact of participation of RC’s in price-based (PB) and incentive-based (IB) DR programs is investigated using game theory. For this, an energy management optimization problem (EMOP) is formulated to minimize electricity cost. The utility company employs electricity price as a linear function of aggregated load in the PB DR program and an incentive rate in the IBDR program. RCs are categorized into active and passive users. Active users are further distinguished based on the ownership of energy storage devices (SD) and dispatchable generation units (DGU). EMOP is modeled using a non-cooperative game, and the distributed proximal decomposition method is used to obtain the Nash equilibrium of the game. The results of the proposed approach are analyzed using different case studies. The performance of the proposed approach is evaluated in terms of aggregated cost and system load profile. It has been observed that participation in PB and IBDR program benefits both the utility and the consumers.

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