Development of hybrid microgrid model for frequency stabilization

2017 ◽  
Vol 41 (5) ◽  
pp. 343-352 ◽  
Author(s):  
A Jeya Veronica ◽  
N Senthil Kumar
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Fossil Fuels ◽  
Energy Sources ◽  
Frequency Regulation ◽  
Diesel Generator ◽  
Distributed Energy ◽  
Hybrid Microgrid ◽  
Battery Energy Storage Systems ◽  
Battery Energy

Power systems of today are highly complex and highly interconnected. It generates electricity by burning fossil fuels (coal, natural gas, diesel, nuclear fuel, etc.), which produces harmful gases and particles, pollutes environment, and degrades lives. To mitigate the bad impact of burning fossil fuels and meet the increase in electrical system, demand distributed energy sources employing nonconventional energy sources like wind and solar are used. Electric power generation through the nonconventional energy sources has become more viable and cheaper than the fossil fuel–based power plants. This article explores the development of a microgrid model incorporating wind turbine generators, diesel generator, fuel cells, aqua electrolyzers, and battery energy storage systems. An optimization scheme for fixing the proportional–integral controller parameters of frequency regulation is developed for different possible combinations of wind power with other distributed energy resources in the microgrid.

scholarly journals Life Cycle Estimation of Battery Energy Storage Systems for Primary Frequency Regulation

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3320 ◽  
Author(s):  
Natascia Andrenacci ◽  
Elio Chiodo ◽  
Davide Lauria ◽  
Fabio Mottola
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Control Strategy ◽  
Storage Systems ◽  
The State ◽  
Frequency Regulation ◽  
Battery Energy Storage ◽  
Battery Lifetime ◽  
Battery Energy Storage Systems ◽  
Battery Energy

An increasing share of renewable energy sources in power systems requires ad-hoc tools to guarantee the closeness of the system’s frequency to its rated value. At present, the use of new technologies, such as battery energy storage systems, is widely debated for its participation in the service of frequency containment. Since battery installation costs are still high, the estimation of their lifetime appears crucial in both the planning and operations of power systems’ regulation service. As the frequency response of batteries is strongly dependent on the stochastic nature of the various contingencies which can occur on power systems, the estimation of the battery lifetime is a very complex issue. In the present paper, the stochastic process which better represents the power system frequency is analyzed first; then the battery lifetime is properly estimated on the basis of realistic dynamic modeling including the state of the charge control strategy. The dynamic evolution of the state of charge is then used in combination with the celebrated rain-flow procedure with the aim of evaluating the number of charging/discharging cycles whose knowledge allows estimating the battery damage. Numerical simulations are carried out in the last part of the paper, highlighting the resulting lifetime probabilistic expectation and the impact of the state of the charge control strategy on the battery lifetime. The main findings of the present work are the proposed autoregressive model, which allows creating accurate pseudo-samples of frequency patterns and the analysis of the incidence of the control law on the battery lifetime. The numerical applications clearly show the prominent importance of this last aspect since it has an opposing impact on the economic issue by influencing the battery lifetime and technical effects by modifying the availability of the frequency regulation service.

scholarly journals Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

2021 ◽  
Author(s):  
Chinmay Shah ◽  
Richard Wies ◽  
Jennifer King
Keyword(s):  
Power Systems ◽  
Information Exchange ◽  
Optimization Problem ◽  
Distributed Optimization ◽  
Communication Overhead ◽  
Distributed Energy ◽  
Central Controller ◽  
Alternating Direction ◽  
Battery Energy Storage Systems ◽  
Battery Energy

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, which limits the size of the problem that can be solved, and also creates a high communication overhead since all the data is transferred to the central controller. These limitations are addressed by a proposed consensus-ADMM (alternating direction method of multiplier) based distributed optimization algorithm, which decomposes the optimization problem into sub-problems. The distribution feeder is partitioned into low coupling sub-networks/regions, which solves the sub-problem locally and exchanges information with the neighboring regions to reach consensus to solve for the global update. The information exchange and synchronization between sub-networks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a virtual aggregator for synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for 0.5-MW laboratory microgrid for one hour ahead and day-ahead for IEEE 123-bus and EPRI J1 test feeder, and results are compared with a centralized solution.

scholarly journals FEATURES OF THE USE OF HYDROELECTRIC POWER PLANTS AND BATTERY ENERGY STORAGE SYSTEMS FOR FREQUENCY STABILIZATION IN POWER SYSTEMS

2018 ◽  
pp. 3-11 ◽  
Author(s):  
M.M. Kulyk ◽  
O.V. Zgurovets
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Storage Systems ◽  
Hydroelectric Power ◽  
Battery Energy Storage ◽  
Hydroelectric Power Plants ◽  
Battery Energy Storage Systems ◽  
Battery Energy

A mathematical model of frequency and power regulation in power systems with large wind power plants (WPPs), hydroelectric power plants (HPPs), and battery energy storage systems (BESSs) was developed. Using this model, we carried out a complex of studies over a wide range of changes in the power of HPPs, BESSs, and their proportions. Options are considered when HPP and BESS work separately. The conditions under which HPPs and BESSs provide a stable operation of the power system, working separately with satisfying the requirements to frequency deviation in the integrated power system of Ukraine and in the ENTSO-E energy system of the European Union are determined. A series of calculations for the joint use of HPPs and BESSs was carried out, and, as a result, recommendations were formulated on the conditions for joint operation of HPPs and BESSs. Bibl. 6, Fig. 4, Tab. 5.

scholarly journals Consensus-Based ADMM for Distributed Optimization in Power Systems using Private Blockchain Network

2021 ◽  
Author(s):  
Chinmay Shah ◽  
Richard Wies ◽  
Jennifer King
Keyword(s):  
Power Systems ◽  
Information Exchange ◽  
Optimization Problem ◽  
Distributed Optimization ◽  
Communication Overhead ◽  
Distributed Energy ◽  
Central Controller ◽  
Alternating Direction ◽  
Battery Energy Storage Systems ◽  
Battery Energy

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, which limits the size of the problem that can be solved, and also creates a high communication overhead since all the data is transferred to the central controller. These limitations are addressed by a proposed consensus-ADMM (alternating direction method of multiplier) based distributed optimization algorithm, which decomposes the optimization problem into sub-problems. The distribution feeder is partitioned into low coupling sub-networks/regions, which solves the sub-problem locally and exchanges information with the neighboring regions to reach consensus to solve for the global update. The information exchange and synchronization between sub-networks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a virtual aggregator for synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for 0.5-MW laboratory microgrid for one hour ahead and day-ahead for IEEE 123-bus and EPRI J1 test feeder, and results are compared with a centralized solution.

scholarly journals Application of Battery Energy Storage Systems for Primary Frequency Control in Power Systems with High Renewable Energy Penetration

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1379
Author(s):  
Md Ruhul Amin ◽  
Michael Negnevitsky ◽  
Evan Franklin ◽  
Kazi Saiful Alam ◽  
Seyed Behzad Naderi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Storage Systems ◽  
Frequency Control ◽  
Battery Energy Storage ◽  
Battery Energy Storage Systems ◽  
Battery Energy ◽  
Primary Frequency ◽  
Primary Frequency Control

In power systems, high renewable energy penetration generally results in conventional synchronous generators being displaced. Hence, the power system inertia reduces, thus causing a larger frequency deviation when an imbalance between load and generation occurs, and thus potential system instability. The problem associated with this increase in the system’s dynamic response can be addressed by various means, for example, flywheels, supercapacitors, and battery energy storage systems (BESSs). This paper investigates the application of BESSs for primary frequency control in power systems with very high penetration of renewable energy, and consequently, low levels of synchronous generation. By re-creating a major Australian power system separation event and then subsequently simulating the event under low inertia conditions but with BESSs providing frequency support, it has been demonstrated that a droop-controlled BESS can greatly improve frequency response, producing both faster reaction and smaller frequency deviation. Furthermore, it is shown via detailed investigation how factors such as available battery capacity and droop coefficient impact the system frequency response characteristics, providing guidance on how best to mitigate the impact of future synchronous generator retirements. It is intended that this analysis could be beneficial in determining the optimal BESS capacity and droop value to manage the potential frequency stability risks for a future power system with high renewable energy penetrations.

scholarly journals Co-Optimizing Battery Storage for Energy Arbitrage and Frequency Regulation in Real-Time Markets Using Deep Reinforcement Learning

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8365
Author(s):  
Yushen Miao ◽  
Tianyi Chen ◽  
Shengrong Bu ◽  
Hao Liang ◽  
Zhu Han
Keyword(s):  
Real Time ◽  
Critical Role ◽  
Frequency Regulation ◽  
Power Networks ◽  
Physical Constraints ◽  
Policy Gradient ◽  
Markov Decision ◽  
Battery Energy Storage Systems ◽  
Complex Decision Making ◽  
Battery Energy

Battery energy storage systems (BESSs) play a critical role in eliminating uncertainties associated with renewable energy generation, to maintain stability and improve flexibility of power networks. In this paper, a BESS is used to provide energy arbitrage (EA) and frequency regulation (FR) services simultaneously to maximize its total revenue within the physical constraints. The EA and FR actions are taken at different timescales. The multitimescale problem is formulated as two nested Markov decision process (MDP) submodels. The problem is a complex decision-making problem with enormous high-dimensional data and uncertainty (e.g., the price of the electricity). Therefore, a novel co-optimization scheme is proposed to handle the multitimescale problem, and also coordinate EA and FR services. A triplet deep deterministic policy gradient with exploration noise decay (TDD–ND) approach is used to obtain the optimal policy at each timescale. Simulations are conducted with real-time electricity prices and regulation signals data from the American PJM regulation market. The simulation results show that the proposed approach performs better than other studied policies in literature.

scholarly journals Design of Combined Stationary and Mobile Battery Energy Storage Systems

2021 ◽  
Author(s):  
Hassan Hayajneh ◽  
Xuewei Zhang
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage Systems ◽  
Design Parameters ◽  
Frequency Regulation ◽  
Energy Storage Systems ◽  
Battery Energy Storage ◽  
Battery Capacity ◽  
Battery Energy Storage Systems ◽  
Battery Energy

To minimize the curtailment of renewable generation and incentivize grid-scale energy storage deployment, a concept of combining stationary and mobile applications of battery energy storage systems built within renewable energy farms is proposed. A simulation-based optimization model is developed to obtain the optimal design parameters such as battery capacity and power ratings by solving a multi-objective optimization problem that aims to maximize the economic profitability, the energy provided for transportation electrification, the demand peak shaving, and the renewable energy utilized. Two applications considered for the stationary energy storage systems are the end-consumer arbitrage and frequency regulation, while the mobile application envisions a scenario of a grid-independent battery-powered electric vehicle charging station network. The charging stations receive supplies from the energy storage system that absorbs renewable energy, contributing to a sustained DC demand that helps with revenues. Representative results are presented for two operation modes and different sets of weights assigned to the objectives. Substantial improvement in the profitability of combined applications over single stationary applications is shown. Pareto frontier of a reduced dimensional problem is obtained to show the trade-off between design objectives. This work could pave the road for future implementations of the new form of energy storage systems.<br>

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