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 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 Novel Algorithm with Multiple Consumer Demand Response Priorities in Residential Unbalanced LV Electricity Distribution Networks

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1220
Author(s):  
Ovidiu Ivanov ◽  
Samiran Chattopadhyay ◽  
Soumya Banerjee ◽  
Bogdan-Constantin Neagu ◽  
Gheorghe Grigoras ◽  
...  
Keyword(s):  
Demand Response ◽  
Distribution System ◽  
Smart Grids ◽  
Low Voltage ◽  
Distribution Networks ◽  
Load Flow ◽  
Electricity Distribution ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Novel Algorithm

Demand Side Management (DSM) is becoming necessary in residential electricity distribution networks where local electricity trading is implemented. Amongst the DSM tools, Demand Response (DR) is used to engage the consumers in the market by voluntary disconnection of high consumption receptors at peak demand hours. As a part of the transition to Smart Grids, there is a high interest in DR applications for residential consumers connected in intelligent grids which allow remote controlling of receptors by electricity distribution system operators and Home Energy Management Systems (HEMS) at consumer homes. This paper proposes a novel algorithm for multi-objective DR optimization in low voltage distribution networks with unbalanced loads, that takes into account individual consumer comfort settings and several technical objectives for the network operator. Phase load balancing, two approaches for minimum comfort disturbance of consumers and two alternatives for network loss reduction are proposed as objectives for DR. An original and faster method of replacing load flow calculations in the evaluation of the feasible solutions is proposed. A case study demonstrates the capabilities of the algorithm.

scholarly journals A Low-Voltage DC Backbone with Aggregated RES and BESS: Benefits Compared to a Traditional Low-Voltage AC System

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1420
Author(s):  
Hakim Azaioud ◽  
Robbert Claeys ◽  
Jos Knockaert ◽  
Lieven Vandevelde ◽  
Jan Desmet
Keyword(s):  
Low Voltage ◽  
Distribution Grid ◽  
Battery Energy Storage ◽  
Pv Systems ◽  
Self Sufficiency ◽  
Battery Energy Storage Systems ◽  
Consumption Index ◽  
Promising Solution ◽  
Battery Energy ◽  
Pv Penetration

The increasing penetration of PV into the distribution grid leads to congestion, causing detrimental power quality issues. Moreover, the multiple small photovoltaic (PV) systems and battery energy storage systems (BESSs) result in increasing conversion losses. A low-voltage DC (LVDC) backbone to interconnect these assets would decrease the conversion losses and is a promising solution for a more optimal integration of PV systems. The multiple small PV systems can be replaced by shared assets with large common PV installations and a large BESS. Sharing renewable energy and aggregation are activities that are stimulated by the European Commission and lead to a substantial benefit in terms of self-consumption index (SCI) and self-sufficiency index (SSI). In this study, the benefit of an LVDC backbone is investigated compared to using a low-voltage AC (LVAC) system. It is found that the cable losses increase by 0.9 percent points and the conversion losses decrease by 12 percent points compared to the traditional low-voltage AC (LVAC) system. The SCI increases by 2 percent points and the SSI increases by 6 percent points compared to using an LVAC system with shared meter. It is shown that an LVDC backbone is only beneficial with a PV penetration level of 65% and that the BESS can be reduced by 22% for the same SSI.

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 Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3369
Author(s):  
Maria C. Fotopoulou ◽  
Panagiotis Drosatos ◽  
Stefanos Petridis ◽  
Dimitrios Rakopoulos ◽  
Fotis Stergiopoulos ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Urban Areas ◽  
Pv Systems ◽  
Node Distribution ◽  
Building Integrated Photovoltaic ◽  
Battery Energy Storage Systems ◽  
Main Components ◽  
Battery Energy

This paper introduces a Model Predictive Control (MPC) strategy for the optimal energy management of a district whose buildings are equipped with vertically placed Building Integrated Photovoltaic (BIPV) systems and Battery Energy Storage Systems (BESS). The vertically placed BIPV systems are able to cover larger areas of buildings’ surfaces, as compared with conventional rooftop PV systems, and reach their peak of production during winter and spring, which renders them suitable for energy harvesting especially in urban areas. Driven by both these relative advantages, the proposed strategy aims to maximize the district’s autonomy from the external grid, which is achieved through the cooperation of interactive buildings. Therefore, the major contribution of this study is the management and optimal cooperation of a group of buildings, each of which is equipped with its own system of vertical BIPV panels and BESS, carried out by an MPC strategy. The proposed control scheme consists of three main components, i.e., the forecaster, the optimizer and the district, which interact periodically with each other. In order to quantitatively evaluate the benefits of the proposed MPC strategy and the implementation of vertical BIPV and BESS, a hypothetical five-node distribution network located in Greece for four representative days of the year was examined, followed by a sensitivity analysis to examine the effect of the system configuration on its performance.

scholarly journals Towards a Smart Low Voltage Distribution System: An Indian Experience

2021 ◽  
Author(s):  
Ramanuja Panigrahi ◽  
Santanu Mishra ◽  
Suresh C. Srivastava ◽  
Prasad Enjeti
Keyword(s):  
Distribution System ◽  
Smart Home ◽  
Architectural Design ◽  
Low Voltage ◽  
Voltage Distribution ◽  
Solid State Transformers ◽  
Power Exchange ◽  
Distribution Transformers ◽  
Operational Issues ◽  
Distribution Grids

<em>Realizing a smart Low Voltage Distribution System (LVDS) is essential to realize a smart grid. Restructuring the existing distribution system into microgrids is one important requirement to achieve a smart LVDS. The realization of microgrids in LVDS can take different shapes in different countries. This article discusses the challenges and practical solutions to realize a smart LVDS for radial distribution grids, which are common in India. The network following a distribution transformer can be distinguished as a microgrid for radial low voltage distribution grids. However, this leads to many operational issues. Therefore, this article envisions replacing the Low Voltage distribution transformers with <a>Solid-State Transformers </a>(SSTs). This will enable the LVDS to control the power exchange between the phases within a microgrid as well as power exchange between different microgrids. The architectural design of a smart home in smart LVDS is outlined to complete the discussion. Various unique features required for smart inverters in a smart home and existing grid codes to make them compatible with smart LVDS are also reviewed.</em><i></i>

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 An Innovative Adaptive Droop Control Based on Available Energy for DC Micro Distribution Grids

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2983 ◽  
Author(s):  
Duc Nguyen Huu
Keyword(s):  
Storage Systems ◽  
Energy Levels ◽  
Adaptive Method ◽  
Droop Control ◽  
Available Energy ◽  
Dc Distribution ◽  
Battery Energy Storage Systems ◽  
The Stability ◽  
Battery Energy ◽  
Distribution Grids

DC distribution grids are increasingly a promising solution for wind and solar integration due to good matching with DC output voltage such as photovoltaic (PV) array systems, distributed battery storage systems (BESS) and electric vehicles. To overcome the control problems involving coordination control schemes of multi-BESSs in real-time as well as operation strategies of DC grids in the long-term, this paper presents the effective adaptive coordinated droop control of multi-battery energy storage systems (MBESSs) in DC distribution grids. The adaptive coordinated droop is proposed according to the available energy levels in BESSs. With the proposed method, the dual-objectives, which are stabilization of DC voltages especially through disturbance for instance outage of BESS and enhancement of State of Charge (SOC)-balance speed among BESSs, can be achieved. Analytical derivations are established to investigate the impacts of the adaptive method. Meanwhile, the influence of the proposed method on the stability is presented.

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