A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing

Fanti, Maria Pia; Mangini, Agostino Marcello; Roccotelli, Michele; Ukovich, Walter

doi:10.1109/tase.2015.2472956

Cited by 51 publications

(24 citation statements)

References 30 publications

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“…Fanti et al . studied the heating, ventilation, and air‐conditioning (HVAC) in a district. Xing et al .…”

Section: Literature Reviewmentioning

confidence: 99%

“…They solved the problem by using stochastic programming. The multi‐agent problem is solved in a distributed way . Various solutions have been proposed at the second level of multi‐agent problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this study, we considered community energy management systems (CEMSs) . A CEMS stands between energy consumers in a community and energy suppliers, and provides ancillary service to the former.…”

Section: Introductionmentioning

confidence: 99%

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Distributed day‐ahead scheduling in community energy management systems using inter‐community energy trade

Murakami

Okada

Fukuda

et al. 2018

IEEJ Transactions Elec Engng

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A community energy management system (CEMS) stands between energy consumers in a community and energy suppliers, and provides ancillary service to the former. A CEMS performs day-ahead scheduling for its energy conversion equipment and energy purchase planning for the next day to minimize energy consumption and cost under some constraints. In this study, we assume that multiple CEMSs can cooperatively perform the aforementioned; we examine a day-ahead scheduling problem among a group of CEMSs using two key solutions for energy saving: demand response and energy trade. Using the demand response, CEMS can change the energy of consumers to improve energy utilization efficiency. Using the energy trade, CEMSs can trade surplus energy with each other. First, we build an optimization problem for a group of CEMSs. Then, the alternating direction method of multipliers is used to decompose the optimization problem into a distributed optimization problem. Results of numerical experiments show that both the demand response and the energy trade cooperatively affect energy saving of the group. MasahiroOkada (Non-member) received the B.E. and M.E. degrees in electronic and information engineering from Osaka University in 2015 and 2017, respectively. Takuya Fukuda (Student Member) received the B.E. degree in electronic and information engineering from Osaka University in 2016. He is currently working toward the M.S. degree in the Department of Electrical Engineering and Information Systems, Graduate School of Engineering, University of Tokyo. His research interests include optimal control systems for electric vehicle. Shoichi Kitamura (Member) received the B.E. and M.E. degrees in biophysical engineering and the Dr. of Eng. degree in electrical engineering from Osaka University in 2000 and 2002, and 2013, respectively. He joined the Advanced Technology R&D Center, Mitsubishi Electric Corporation, Hyogo, in 2002, where he was engaged in research on the factory energy management system. At present, he is engaged in research on smart grid and smart community-related technologies.

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“…Fanti et al . studied the heating, ventilation, and air‐conditioning (HVAC) in a district. Xing et al .…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Distributed day‐ahead scheduling in community energy management systems using inter‐community energy trade

Murakami

Okada

Fukuda

et al. 2018

IEEJ Transactions Elec Engng

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“…Many optimisation models have been studied in the literature for operational planning and control in district heating systems (DHS). In [21,26], the authors presented energy management strategies to optimise the energy distribution of smart buildings in districts, with the aim to limit wastes and costs, while respecting the users' comfort preferences. Mixed-integer programming with mathematical models and Lagrangian relaxation based algorithms is proposed in [27], for short-term production planning in co-generation and power systems.…”

Section: Current Control Approaches In Dhc Systemsmentioning

confidence: 99%

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

et al. 2019

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This paper presents a holistic innovative solution for the transformation of the current district heating and cooling systems to automated more efficient systems. A variety of technological advancements have been developed and integrated to support the effective energy management of future district heating and cooling sector. First, we identify and discuss the main challenges and needs that are in line with the EU objectives and policy expectations. We give an overview of the main parts that our solution consists of, with emphasis on the forecasting tools and an advanced control system that addresses unit commitment and economic load dispatch problems. The proposed control approach employs distributed and scalable optimisation algorithms for optimising the short-term operations of a district heating and cooling plant subject to technical constraints and uncertainties in the energy demand. To test the performance and validate the proposed control system, a district heating plant with multiple energy generation units and real-life heat load data were used. Simulation experiments were also used to evaluate the benefits of using thermal storage units in district heating systems. The results show that the proposed method could achieve significant cost savings when energy storage is employed. The proposed control strategy can be applied for both operating optimally district heating plants with storage and supporting investment planning for new storage units.

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“…A generic optimal industrial load management scheme compatible with energy hub management systems was developed in [3] for process scheduling in industries such as flour mills and water pumping facilities. The mixed logical dynamical (MLD) approach was used to formulate and solve an optimal scheduling problem for district heating networks including generation sources, thermal energy storage systems, and flexible thermal loads in [5]. A load management strategy meeting objectives such as maximum user comfort or minimum cost for thermostatically controlled household appliances was presented in [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

et al. 2018

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This paper proposes an efficient energy management system (EMS) for industrial microgrids (MGs). Many industries deploy large pumps for their processes. Oftentimes, such pumps are operated during hours of peak electricity prices. A lot of industries use a mix of captive generation and imported utility electricity to meet their energy requirements. The MG considered in this paper includes diesel generators, battery energy storage systems, renewable energy sources, flexible loads, and interruptible loads. Pump loads found in shipyard dry docks are modelled as exemplar flexible industrial loads. The proposed EMS has a two-stage architecture. An optimal MG scheduling problem including pump scheduling and curtailment of interruptible loads (ILs) is formulated and solved in the first stage. An optimal power flow problem is solved in the second stage to verify the feasibility of the MG schedule with the network constraints. An iterative procedure is used to coordinate the two EMS stages. Multiple case studies are used to demonstrate the utility of the proposed EMS. The case studies highlight the efficacy of load management strategies such as pump scheduling and curtailment of ILs in reducing the total electricity cost of the MG.

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A District Energy Management Based on Thermal Comfort Satisfaction and Real-Time Power Balancing

Cited by 51 publications

References 30 publications

Distributed day‐ahead scheduling in community energy management systems using inter‐community energy trade

Distributed day‐ahead scheduling in community energy management systems using inter‐community energy trade

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

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