A multi-agent based energy management solution for integrated buildings and microgrid system

Anvari‐Moghaddam, Amjad; Rahimi-Kian, Ashkan; Mirian, Maryam S.

doi:10.1016/j.apenergy.2017.06.007

Cited by 235 publications

(118 citation statements)

References 39 publications

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…Anvari-Moghaddam et al [70] presented an energy management system for a microgrid that includes houses and buildings. The optimization process for the energy management system involves the coordination of management in distributed generation (DG) and response to the demand.…”

Section: Energy Management Based On Multi-agent Systemsmentioning

confidence: 99%

Energy Management in Microgrids with Renewable Energy Sources: A Literature Review

2019

View full text Add to dashboard Cite

Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed.

show abstract

Section: Energy Management Based On Multi-agent Systemsmentioning

confidence: 99%

Energy Management in Microgrids with Renewable Energy Sources: A Literature Review

2019

View full text Add to dashboard Cite

show abstract

“…In addition, the research results of Adam's research team in the field of integrated energy systems are also worth learning, especially in operation management and scheduling of energy systems, the regional interconnection of energy systems, and risk research. In terms of operation management and scheduling of energy systems, an ontology‐driven multi‐agent based energy management system is proposed for monitoring and optimal control of an integrated homes/buildings and microgrid system, 14,15 an efficient strategy is developed to control local operation of each microgrid including the amount of energy to be requested from the main grid and the optimal charging/discharging patterns of batteries along with the transferred power among microgrids considering system's technical constraints, 16 a novel multi‐objective bidding strategy framework is proposed for a wind‐thermal photovoltaic system in the deregulated electricity market, 17 an optimization framework is developed for optimal operation of a CHP system in an uncertain environment considering demand response actions, 18 a conventional waste‐driven combined heat and power cycle is combined with a large‐scale absorption chiller to not only create a strong yet reliable synergy between the three energy sectors of cold, heat, and power, but also to improve the plant performance in terms of energy and sustainability indices 19 . In terms of risk research, a risk‐constrained scheduling optimization model is presented for a grid‐connected hybrid microgrid including demand response, electric vehicles, variable wind power generation, and dispatchable generation units, 20 a hierarchical stochastic energy management system is proposed for operation management of interconnected microgrids, 21 a novel stochastic model is presented from a microgrid operator perspective for energy and reserve scheduling considering risk management strategy 22 .…”

Section: Introductionmentioning

confidence: 99%

Cross‐regional integrated energy system scheduling optimization model considering conditional value at risk

Zheng

2020

Int J Energy Res

View full text Add to dashboard Cite

Integrated energy system is a very important way to improve energy efficiency. Based on the combined heating cooling and power system, combined with energy storage equipment, a cross-regional integrated energy system scheduling optimization problem is studied. An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region. Meanwhile, the value at risk (VaR) theory is introduced and the operating constraints of equipment in the integrated energy system fully considered, the integrated energy system scheduling model with VaR is established. The example shows that the model can realize multi-type electrical, heating, and cooling load optimized by schedule across regions under the premise of satisfying the balance of energy supply and demand, which can reduce the system operation cost. The sensitivity analysis of the minimum expected cost and the influencing factors of conditional VaR is carried out to verify the validity and feasibility of the proposed model. K E Y W O R D SCCHP, conditional value at risk, cross-region, integrated energy system, scheduling optimization

show abstract

“…Also, a distributed P/EMS suffers from degradation of performance on small/medium networks, increased use of database space, and complex use and administration. Multi-agent system (MAS) is one of the best illustrations for a distributed scheme [44]. …”

Section: Distributed P/emsmentioning

confidence: 99%

Optimal Design and Operation Management of Battery-Based Energy Storage Systems (BESS) in Microgrids

Anvari‐Moghaddam¹,

Dulout

Alonso

et al. 2018

Advancements in Energy Storage Technologies

Self Cite

View full text Add to dashboard Cite

Energy storage systems (ESSs) can enhance the performance of energy networks in multiple ways; they can compensate the stochastic nature of renewable energies and support their large-scale integration into the grid environment. Energy storage options can also be used for economic operation of energy systems to cut down system's operating cost. By utilizing ESSs, it is very possible to store energy in off-peak hours with lower cost and energize the grid during peak load intervals avoiding high price spikes. Application of ESSs will also enable better utilization of distributed energy sources and provide higher controllability at supply/demand side which is helpful for load leveling or peak shaving purposes. Last but not least, ESSs can provide frequency regulation services in off-grid locations where there is a strong need to meet the power balance in different operating conditions. Each of the abovementioned applications of energy storage units requires certain performance measures and constraints, which has to be well considered in design phase and embedded in control and management strategies. This chapter mainly focuses on these aspects and provides a general framework for optimal design and operation management of battery-based ESSs in energy networks.

show abstract

A multi-agent based energy management solution for integrated buildings and microgrid system

Cited by 235 publications

References 39 publications

Energy Management in Microgrids with Renewable Energy Sources: A Literature Review

Energy Management in Microgrids with Renewable Energy Sources: A Literature Review

Cross‐regional integrated energy system scheduling optimization model considering conditional value at risk

Optimal Design and Operation Management of Battery-Based Energy Storage Systems (BESS) in Microgrids

Contact Info

Product

Resources

About