Aggregate modeling and coordination of diverse energy resources under packetized energy management

Author(s):  
Luis A. Duffaut Espinosa ◽  
Mads Almassalkhi ◽  
Paul Hines ◽  
Jeff Frolik
Thermo ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 63-76
Author(s):  
Mengxuan Yan ◽  
Dongxiao Wang ◽  
Chun Sing Lai ◽  
Loi Lei Lai

Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Deyaa Ahmed ◽  
Mohamed Ebeed ◽  
Abdelfatah Ali ◽  
Ali S. Alghamdi ◽  
Salah Kamel

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.


2021 ◽  
Vol 22 (1) ◽  
pp. 85-100
Author(s):  
Suchitra Dayalan ◽  
Rajarajeswari Rathinam

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.


2021 ◽  
Vol 4 (2) ◽  
pp. 125-130
Author(s):  
Muhammad Azhar Mahmood ◽  
Muhammad Kamran Liaqat Bhatti ◽  
S. Raza ◽  
M. Riaz

Most of the industries including the oil sector are looking forward towards the renewable energy resources with proper energy management system (EMS) as it is the need of time. For this purpose, solar and wind energy are the renewable energy resources, which are obtained from natural resources and produce clean and environment -friendly electrical energy and can be used for oil depots. The proper utilization of solar and wind energy from natural resource may result in economical and cost-effective EMS. In the proposed research work, an effective energy management demonstration is delivered to ensure the ceaseless flexibility of power. Furthermore, reduction of production per unit cost to the oil sector industry by utilizing multiple objectives streamlining. In the proposed oil depot, connected loads are divided into Shiftable and Non-Shiftable loads and then apply Branch and Bound Algorithm (BnB) with binary integer linear programming (BILP). By using the BnB technique, selected shiftable loads are shifted to the low cost energy resource automatically and resultantly, we get the low price unit cost and continuous power supply. Simulation results for the above-mentioned research work are performed on MATLAB. The proposed technique helps to reduce the power stack shedding issue as well.


Author(s):  
Monika Gaba ◽  
Saurabh Chanana

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.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 145757-145766 ◽  
Author(s):  
Bomiao Liang ◽  
Weijia Liu ◽  
Lei Sun ◽  
Zhiyuan He ◽  
Beiping Hou

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3039 ◽  
Author(s):  
Luu An ◽  
Tran Tuan

With the dramatic development of renewable energy resources all over the world, Vietnam has started to apply them along with the conventional resources to produce the electrical power in recent years. Visually, the aim of this action is to improve the economic as well as the environmental benefits. Therefore, a vast of hybrid systems that combine Wind turbine, Photovoltaic (PV), Diesel generator and battery have been considered with different configurations. According to this topic, there are lots of research trends in the literature. However, we aim to the optimal energy management of this hybrid system. In particular, in this paper, we propose an optimization method to deal with it. The interesting point of the proposed method is the usage of the information of sources, loads, and electricity market as an embedded forecast step to enhance the effectiveness of the actual operation via minimizing the operation cost by scheduling distributed energy resources (DER) while regarding emission reduction in the hybrid system is considered as the objective function. In this optimization problem, the constraints are determined by two terms, namely: the balance of power between the supply and the load demand, and also the limitations of each DER. Thus, to solve this problem, we make use of the dynamic programming (DP) to transform a system into a multi-stage decision procedure with respect to the state of charge (SOC), resulting in the minimum system cost (CS). In order to highlight the pros of the proposed method, we implement the comparison to a rule-based method in the same context. The simulation results are examined in order to evaluate the effectiveness of the developed methodology, which is a so-called global optimization.


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