scholarly journals Operation of Distributed Battery Considering Demand Response Using Deep Reinforcement Learning in Grid Edge Control

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7749
Author(s):  
Wenying Li ◽  
Ming Tang ◽  
Xinzhen Zhang ◽  
Danhui Gao ◽  
Jian Wang
Keyword(s):  
Reinforcement Learning ◽  
Demand Response ◽  
Life Cycle Cost ◽  
Low Voltage ◽  
Cost Model ◽  
Voltage Transformer ◽  
Markov Decision ◽  
Battery Energy Storage Systems ◽  
Phase Balance ◽  
Battery Energy

Battery energy storage systems (BESSs) are able to facilitate economical operation of the grid through demand response (DR), and are regarded as the most significant DR resource. Among them, distributed BESS integrating home photovoltaics (PV) have developed rapidly, and account for nearly 40% of newly installed capacity. However, the use scenarios and use efficiency of distributed BESS are far from sufficient to be able to utilize the potential loads and overcome uncertainties caused by disorderly operation. In this paper, the low-voltage transformer-powered area (LVTPA) is firstly defined, and then a DR grid edge controller was implemented based on deep reinforcement learning to maximize the total DR benefits and promote three-phase balance in the LVTPA. The proposed DR problem is formulated as a Markov decision process (MDP). In addition, the deep deterministic policy gradient (DDPG) algorithm is applied to train the controller in order to learn the optimal DR strategy. Additionally, a life cycle cost model of the BESS is established and implemented in the DR scheme to measure the income. The numerical results, compared to deep Q learning and model-based methods, demonstrate the effectiveness and validity of the proposed method.

scholarly journals Incentive Price-Based Demand Response in Active Distribution Grids

2020 ◽  
Vol 11 (1) ◽  
pp. 180
Author(s):  
Karthikeyan Nainar ◽  
Jayakrishnan Radhakrishna Pillai ◽  
Birgitte Bak-Jensen
Keyword(s):  
Power Consumption ◽  
Demand Response ◽  
Distribution System ◽  
Low Voltage ◽  
Pv Systems ◽  
Home Energy Management ◽  
Demand Response Program ◽  
Battery Energy Storage Systems ◽  
Battery Energy ◽  
Distribution Grids

Integration of PV power generation systems at distribution grids, especially at low-voltage (LV) grids, brings in operational challenges for distribution system operators (DSOs). These challenges include grid over-voltages and overloading of cables during peak PV power production. Battery energy storage systems (BESS) are being installed alongside PV systems by customers for smart home energy management. This paper investigates the utilization of those BESS by DSOs for maintaining the grid voltages within limits. In this context, an incentive price based demand response (IDR) method is proposed for indirect control of charging/discharging power of the BESS according to the grid voltage conditions. It is shown that the proposed IDR method, which relies on a distributed computing application, is able to maintain the grid voltages within limits. The advantage of the proposed distributed implementation is that the DSOs can compute and communicate the incentive prices thereby encouraging customers to actively participate in the demand response program. An iterative distributed algorithm is used to compute the incentive prices of individual BESS to minimize the costs of net power consumption of the customer. The proposed IDR method is tested by conducting simulation studies on the model of a Danish LV grid for few study cases. The simulation results show that by using the proposed method for the control of BESS, node voltages are maintained within limits as well as the costs of net power consumption of BESS owners are minimized.

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 An Overview of Bidirectional AC-DC Grid Connected Converter Topologies for Low Voltage Battery Integration

2018 ◽  
Vol 9 (3) ◽  
pp. 1223 ◽  
Author(s):  
Kaspars Kroics ◽  
Oleksandr Husev ◽  
Kostiantyn Tytelmaier ◽  
Janis Zakis ◽  
Oleksandr Veligorskyi
Keyword(s):  
Energy Storage ◽  
High Efficiency ◽  
Low Voltage ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Distribution Grid ◽  
Battery Energy Storage ◽  
Battery Energy Storage Systems ◽  
Converter Topologies ◽  
Battery Energy

<p>Battery energy storage systems are becoming more and more popular solution in the household applications, especially, in combination with renewable energy sources. The bidirectional AC-DC power electronic converter have great impact to the overall efficiency, size, mass and reliability of the storage system. This paper reviews the literature that deals with high efficiency converter technologies for connecting low voltage battery energy storage to an AC distribution grid. Due to low voltage of the battery isolated bidirectional AC-DC converter or a dedicated topology of the non isolated converter is required. Review on single stage, two stage power converters and integrated solutions are done in the paper.</p>

scholarly journals Literature review of BESS implementation in DER

2019 ◽  
Vol 16 (2) ◽  
pp. 321-326
Author(s):  
Edwin Rivas Trujillo ◽  
Jesús M López Lezama ◽  
Tays Estefanía Gutiérrez Castro
Keyword(s):  
Energy Storage ◽  
Distributed Generation ◽  
Electric Vehicles ◽  
Demand Response ◽  
Distribution System ◽  
Energy Resources ◽  
Distributed Energy ◽  
Fundamental Part ◽  
Battery Energy Storage Systems ◽  
Battery Energy

Distributed Energy Resources (DER) have been a fundamental part of the inclusion of Battery Energy Storage Systems (BESS) in the generation and distribution system. This work shows an exhaustive review of the different approaches that the authors have developed when implementing BESS in DER, its scope and applications in different environments, observing that the most covered topics are Smart Grid (SG), Distributed Generation (DG), Energy Storage (ES) and where little information is found on the topics of Electric Vehicles (EV), Advanced Measurement (AM) and Demand Response (DR), this is to give an overview of the progress the authors have had and it allows to know in which field of application less information is found, facilitating the search for new researchers.

scholarly journals A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids

2018 ◽  
Vol 8 (3) ◽  
pp. 455 ◽  
Author(s):  
Guido Carpinelli ◽  
Fabio Mottola ◽  
Daniela Proto ◽  
Angela Russo ◽  
Pietro Varilone
Keyword(s):  
Energy Storage ◽  
Hybrid Method ◽  
Low Voltage ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Battery Energy Storage ◽  
Battery Energy Storage Systems ◽  
Battery Energy
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