Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings

Zou, Bin; Peng, Jinqing; Li, Sihui; Li, Yang; Yan, Jinyue; Yang, Hongxing

doi:10.1016/j.apenergy.2021.117875

Cited by 65 publications

(24 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The purpose of each technology may be related to the building's thermal needs, e.g., heat pumps and sensible heat storage, or electrical needs, e.g., BIPV panels and BESS [62]. Of course, the presented technologies may be combined in a variety of ways, such as energy harvesting coupled with storage [63] or energy harvesting coupled with air conditioning [64], depending on the building's location, operation, etc.…”

Section: Synopsis Of Adbe Technologiesmentioning

confidence: 99%

State of the Art of Technologies in Adaptive Dynamic Building Envelopes (ADBEs)

et al. 2022

View full text Add to dashboard Cite

The design of adaptive façades as complex systems that dynamically respond to weather conditions and occupants’ demands is rapidly increasing in modern constructions since they are highly energy efficient. Adaptive Dynamic Building Envelopes (ADBEs) exploit the benefits of technologies that manage the energy and mass transfer between building and outdoor environments actively and selectively. There is a wide range of technologies used in the design of ADBEs that differ from one another in terms of user controllability and the level of how active or passive their technologies are. This paper provides a systematic search in literature on the technologies devised in the ADBEs, specifying the most prevalent practices, and highlights the most cutting-edge research approximations. The analysis shows more than half of the studies use photovoltaics (PVs) in their design. Using mechanical ventilation and heat pumps were the next popular choices. Moreover, approximately half of the studies were carried out using simulation methods alone, whereas only 13% of studies couple simulations with experimental work. This highlights a clear gap in coupling digital modeling and simulation software with practical field testing and successful mass production.

show abstract

Section: Synopsis Of Adbe Technologiesmentioning

confidence: 99%

State of the Art of Technologies in Adaptive Dynamic Building Envelopes (ADBEs)

et al. 2022

View full text Add to dashboard Cite

show abstract

“…There are a variety of battery energy storage systems, and they all require one battery or a "bank of batteries", i.e., two or more batteries [4,5]. Among them, the solar photovoltaic (PV) system has become the most commonly used technology in the building sector due to its outstanding advantages of low cost [4], eco-friendliness and ease of integration into buildings [6]. Moreover, solar photovoltaic systems can increase the self-consumption of battery energy storage and therefore contribute to a decentralized renewable electricity system [4,7,8].…”

Section: Introductionmentioning

confidence: 99%

“…There has been a wealth of research on the operational performance of battery energy storage systems [3][4][5][6][7][9][10][11][12][13][14][15][16][17][18]. Focusing on a hybrid energy system based on solar photovoltaics, Khan [17] studied various parameters of economic feasibility, sizing strategies with logical advancement to enhance their utilization, their arrangement, and future prospects.…”

Section: Introductionmentioning

confidence: 99%

“…In this context, appropriate operating schedules are important to achieve the desired performance of a battery energy storage system. In order to achieve either the optimization of the energy cost, investment cost or any economic profitability criteria, many studies explored appropriate operational schedules or strategies based on different objectives over recent years [4][5][6][19][20][21][22][23]. Schram [4] addressed the mismatch in electrical power between electricity supply from a photovoltaic system and household electricity demand.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Evaluation Model on Optimal Operational Schedules for Battery Energy Storage System by Maximizing Self-Consumption Strategy and Genetic Algorithm

2022

View full text Add to dashboard Cite

Building an energy storage system is beneficial when solar panels are not producing sufficient energy. However, there is a major issue in terms of feasibility and efficiency. These limitations could be overcome by the deployment of optimal operational strategies. In previous studies, researchers typically focused on finding problem-solving strategies in such situations with only one or two evaluation indicators, lacking a comprehensive evaluation of the integrated objective. Moreover, few studies propose a general model of battery systems suitable for forecast-based operation scenarios with different energy demand features. Therefore, this study developed a comprehensive evaluation model for the operational schedule optimization of a battery energy storage system with a detailed and holistic analysis as well as practicality in implementation. In order to consume the maximum allowable rate of PV generation as promptly and completely as possible, this model was based on a maximizing self-consumption strategy (MSC). A genetic algorithm was applied to time match PV generation and load demand with full consideration of comprehensive techno-economic indicators and total operation cost as well. The model was validated within a typical American house to select the best battery system according to techno-economic indicators for the three types of batteries analyzed. It was discovered that the three types of batteries including Discover AES, Electriq PowerPod2 and Tesla Powerwall+ could all be considered as options for energy storage, and there exist subtle differences in their technical performance during the short charging and discharging phases. Discover AES has the advantage of using PV generation in a timely manner to suit load demand during the long-term operation of a battery energy storage system. With the proper prediction of building energy demand by means of a machine learning approach, the model’s robustness and predictive performance could be further extended. The machine learning approach proved feasible for adapting our optimization model to various battery storage scenarios with different energy demand features. This study is novel in two ways. Firstly, hierarchical optimization was conducted with a genetic algorithm using the MSC strategy. Secondly, the machine learning approach was applied in conjunction with the genetic algorithm to perform online optimization for the predictive schedule. Additionally, three main advantages of the methodology proposed in this paper for producing an optimal operational schedule were identified, which are as follows: generic applicability, convenient implementation and good scalability. However, the charging and discharging performance of the battery energy storage system was simulated under short-term operation with regular solar radiation. Long-term operation considering solar fluctuation should be investigated in the future.

show abstract

“…The combination of PV and battery (ESS) has advantages to improve the self-consumption rate and mitigate the peak load in the morning and afternoon. The grid-connected PV-battery storage system structure and its strategy to optimize the size of the system, with FIT schemes and an energy management system, have been studied in the related research works [9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Strategy for Grid-Connected PV-Battery System of Mongolian Ger

2022

View full text Add to dashboard Cite

One of the main sources of energy utilized in the Mongolian Gers is coal and wood mainly for the purpose of heating and other domestic use. This heavily increases the air pollution levels. A viable solution for handling the air pollution is switching to renewable energy sources (RES). Grid-connected photovoltaic (PV) systems with battery back-up provide a reliable solution to the problem addressing the energy demand and pollution control. This paper proposes a grid-connected PV–second-life battery system and its operation strategy. A single Ger, which consists of a PV array, battery energy storage system (BESS), and an electric heater (EH), is modeled and tested. The trading coefficient and selling unit price are calculated based on variables such as loan, selling price, and purchasing price. The advantages of the proposed strategy are its simple design and easy implementation. The economic result shows that there is a significant reduction in the electricity bill during winters, while the bill can be reduced to zero during summers. Furthermore, the annual profit from the proposed system is USD 15. The CO2 emissions are reduced from 32 to 7 tCO2.

show abstract

Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings

Cited by 65 publications

References 50 publications

State of the Art of Technologies in Adaptive Dynamic Building Envelopes (ADBEs)

State of the Art of Technologies in Adaptive Dynamic Building Envelopes (ADBEs)

A Comprehensive Evaluation Model on Optimal Operational Schedules for Battery Energy Storage System by Maximizing Self-Consumption Strategy and Genetic Algorithm

A Strategy for Grid-Connected PV-Battery System of Mongolian Ger

Contact Info

Product

Resources

About