Control Strategies of BESS for Compensating Renewable Energy Fluctuations

2012 ◽  
Author(s):  
N.Z. Xu ◽  
Ming Ding ◽  
C.Y. Chung
Keyword(s):  
Renewable Energy ◽  
Control Strategies

scholarly journals A Review of Virtual Inertia Techniques for Renewable Energy-Based Generators

2020 ◽  
Author(s):  
Ana Fernández-Guillamón ◽  
Emilio Gómez-Lázaro ◽  
Eduard Muljadi ◽  
Ángel Molina-Garcia
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Extensive Discussion ◽  
Renewable Sources ◽  
Virtual Inertia ◽  
Alternative Sources

Over recent decades, the penetration of renewable energy sources (RES), especially photovoltaic and wind power plants, has been promoted in most countries. However, as these both alternative sources have power electronics at the grid interface (inverters), they are electrically decoupled from the grid. Subsequently, stability and reliability of power systems are compromised. Inertia in power systems has been traditionally determined by considering all the rotating masses directly connected to the grid. Thus, as the penetration of renewable units increases, the inertia of the power system decreases due to the reduction of directly connected rotating machines. As a consequence, power systems require a new set of strategies to include these renewable sources. In fact, ‘hidden inertia,’ ‘synthetic inertia’ and ‘virtual inertia’ are terms currently used to represent an artificial inertia created by inverter control strategies of such renewable sources. This chapter reviews the inertia concept and proposes a method to estimate the rotational inertia in different parts of the world. In addition, an extensive discussion on wind and photovoltaic power plants and their contribution to inertia and power system stability is presented.

Integration of Renewable Energy in Refrigerated Warehouses

2015 ◽  
pp. 803-853
Author(s):  
Kostadin Fikiin ◽  
Borislav Stankov
Keyword(s):  
Solar Wind ◽  
Renewable Energy ◽  
Energy Supply ◽  
Energy Demand ◽  
Control Strategies ◽  
Public Awareness ◽  
Food Storage ◽  
Policy Makers ◽  
The Public ◽  
And Control

Refrigerated warehouses are large energy consumers and account for a significant portion of the global energy demand. Nevertheless the opportunity for integration of renewable resources in the energy supply of large cold storage facilities is very often unjustifiably neglected, whereas the employment of renewable energy for many other industrial and comfort applications is actively promoted and explored. In that context, the purpose of this chapter is to bridge the existing gap by raising the public awareness of stakeholders, researchers, practicing engineers and policy makers about the availability of a number of smart engineering solutions and control strategies to exploit renewables of different nature (solar, wind, geothermal, biogas, etc.) in the food storage sector, as well as by calling the readers' attention to the specialised knowledge in the matter, which has been published so far.

Smart Grids and Hybrid Energy Storage Systems

2022 ◽  
pp. 779-804
Author(s):  
Muhammad Asif Rabbani
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Smart Grid ◽  
Storage Systems ◽  
Control Strategies ◽  
Energy Systems ◽  
Energy Storage Systems ◽  
Renewable Energy Systems ◽  
Hybrid Energy ◽  
Hybrid Energy Storage

It is very important that the installed renewable energy system should produce the maximum power outputs with minimum costs, and that can only be achieved with the selection of the best optimization technique applied for the best control strategies along with the introduction of the hybrid energy storage systems (HESS). This chapter presents some optimization techniques applied in control strategies for hybrid energy storage systems in distributed renewable energy systems. The integration of energy production and consumption component through the smart grid concept enables increased demand response and energy efficiency. Hybrid energy storage systems and their applications in the renewable energy systems are extensively discussed besides control strategies involved. The storages systems will play an important role in future related to smart grid.

scholarly journals Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 237 ◽  
Author(s):  
Silvio Simani ◽  
Stefano Alvisi ◽  
Mauro Venturini
Keyword(s):  
Renewable Energy ◽  
Model Predictive Control ◽  
Energy Conversion ◽  
Wind Turbine ◽  
Predictive Control ◽  
Control Strategies ◽  
Data Driven ◽  
Control Techniques ◽  
Energy Conversion Systems ◽  
Hydroelectric Plants

The interest in the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this end, data-driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes of working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Therefore, the paper aims at providing some guidelines on the design and the application of different data-driven control strategies to a wind turbine benchmark and a hydroelectric simulator. They rely on self-tuning PID, fuzzy logic, adaptive and model predictive control methodologies. Some of the considered methods, such as fuzzy and adaptive controllers, were successfully verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some details of the implementation of the proposed control strategies to these energy conversion systems. The simulations will highlight that the fuzzy regulators are able to provide good tracking capabilities, which are outperformed by adaptive and model predictive control schemes. The working conditions of the considered processes will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many plants.

Designing Optimal Arbitrage Policies for Distributed Energy Systems in Building Clusters Using Reinforcement Learning

2019 ◽  
Author(s):  
Philip Odonkor ◽  
Kemper Lewis
Keyword(s):  
Renewable Energy ◽  
Reinforcement Learning ◽  
Electricity Markets ◽  
Energy Cost ◽  
Cost Minimization ◽  
Control Strategies ◽  
Cost Savings ◽  
Price Volatility ◽  
Maximization Problem ◽  
Distributed Energy

Abstract In the wake of increasing proliferation of renewable energy and distributed energy resources (DERs), grid designers and operators alike are faced with several emerging challenges in curbing allocative grid inefficiencies and maintaining operational stability. One such challenge relates to the increased price volatility within real-time electricity markets, a result of the inherent intermittency of renewable energy. With this challenge, however, comes heightened economic interest in exploiting the arbitrage potential of price volatility towards demand-side energy cost savings. To this end, this paper aims to maximize the arbitrage value of electricity through the optimal design of control strategies for DERs. Formulated as an arbitrage maximization problem using design optimization, and solved using reinforcement learning, the proposed approach is applied towards shared DERs within multi-building residential clusters. We demonstrate its feasibility across three unique building cluster demand profiles, observing notable energy cost reductions over baseline values. This highlights a capability for generalized learning across multiple building clusters and the ability to design efficient arbitrage policies towards energy cost minimization. Finally, the approach is shown to be computationally tractable, designing efficient strategies in approximately 5 hours of training over a simulation time horizon of 1 month.

scholarly journals A Review on Battery Charging and Discharging Control Strategies: Application to Renewable Energy Systems

Energies ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 1021 ◽  
Author(s):  
Edison Banguero ◽  
Antonio Correcher ◽  
Ángel Pérez-Navarro ◽  
Francisco Morant ◽  
Andrés Aristizabal
Keyword(s):  
Renewable Energy ◽  
Control Strategies ◽  
Energy Systems ◽  
Battery Charging ◽  
Renewable Energy Systems
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