A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building

Moghaddam, Iman Gerami; Saniei, Mohsen; Mashhour, Elaheh

doi:10.1016/j.energy.2015.10.137

Cited by 164 publications

(75 citation statements)

References 27 publications

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“…Schematic representation of proposed energy hub and energy flow . Abbreviations: CHP, combined heat and power; EHP, electrical heat pump…”

Section: Proposed Modelmentioning

confidence: 99%

“…The constraints related to the internal equipments of the S. E. Hubs and their relationship with each other are described in details in Moghaddam et al, and thus, the rewriting of them is avoided in this article; however, they have been used in the simulation.…”

Section: Proposed Modelmentioning

confidence: 99%

“…As explained in Moghaddam et al in detail, because of CHPs cost function, the problem of optimization of EHs is nonlinear and due to having energy storages and not having the possibility of simultaneous charging and discharging of them, the problem is MINLP.…”

Section: Proposed Modelmentioning

confidence: 99%

“…If the constraints of energy distribution grid are not violated, the results of the previous stage are sent to them as FIGURE 1 Schematic representation of proposed energy hub and energy flow. 26 Abbreviations: CHP, combined heat and power; EHP, electrical heat pump the program for the production and exchange of EH. But, if the network constraints are violated, the new work points of S. E. Hubs are determined by the slave program, which is described in the Sections 2 and 3 of this paper.…”

Section: Defining Limitations Of Energy Network In Vppmentioning

confidence: 99%

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Scheduling a smart energy hub-based virtual power plant using benders decomposition to considering power system constraints

Moghaddam

2018

Int Trans Electr Energ Syst

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Summary In this paper, a model is presented for scheduling of a virtual power plant (VPP) which consists of several energy hubs. With a collaborative management of energy hubs as a VPP, collaboration of energy hubs for supplying local loads is managed greatly. Furthermore, the amount of energy exchange with energy distribution networks and limitations of local distribution networks between energy hubs is done via VPP manager. In the presented model, energy hubs can be connected to each other via heat and electricity distribution networks. Using Benders decomposition, scheduling of this VPP is decomposed into a master problem and a slave problem. The master problem defines working points of energy hubs, and the slave problem considers the limitations of energy hubs. The proper performance of the presented model is verified using a case study, and the results are presented in detail.

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“…Schematic representation of proposed energy hub and energy flow . Abbreviations: CHP, combined heat and power; EHP, electrical heat pump…”

Section: Proposed Modelmentioning

confidence: 99%

Section: Proposed Modelmentioning

confidence: 99%

Section: Proposed Modelmentioning

confidence: 99%

Section: Defining Limitations Of Energy Network In Vppmentioning

confidence: 99%

See 2 more Smart Citations

Scheduling a smart energy hub-based virtual power plant using benders decomposition to considering power system constraints

Moghaddam

2018

Int Trans Electr Energ Syst

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“…This case study is devoted to the implementation of the presented framework on a large-scale power system. The test system has 24 generating units including 13 thermal units with valve-point effect, T 1 to T 13 , six CHP units with convex and nonconvex FORs, CHP 14 to CHP 19 , and also five heat-only units, B 20 to B 24 . Tables 9-11 indicate the data of this test system.…”

Section: Case Studymentioning

confidence: 99%

Mixed-integer nonlinear programming framework for combined heat and power units with nonconvex feasible operating region: Feasibility, optimality, and flexibility evaluation

Razavi

Javadi

Nezhad

2018

Int Trans Electr Energ Syst

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This paper presents an optimization framework to determine the optimal operating points of combined heat and power (CHP) units with nonlinear, nonconvex feasible operating region (FOR). The mentioned problem is the economic dispatch (ED) of heat‐only units, thermal units, and CHP units. Also, the electric units are of thermal technology while their valve‐point impact is taken into consideration. Also, the heat power curve of heat‐only units is nonlinear. It is noted that the FOR of CHP units has been defined both as convex and nonconvex regions. For those with nonconvex characteristic, a method is proposed to convert it into a convex characteristic. Accordingly, a separate binary variable must be defined to determine the optimal operating point in each convex region. Thus, the presented problem in this paper is of mixed‐integer nonlinear programming (MINLP) type modeled in General Algebraic Modeling System (GAMS) software. In this respect, different case studies have been presented to assess the optimality, feasibility, and the flexibility of the model. It is noteworthy that the valve‐point effect of thermal units and different FORs of CHP units as well as the electrical power losses have been considered.

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Optimal planning of multi‐energy microgrid with different energy storages and demand responsive loads utilizing a technical‐economic‐environmental programming

2020

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This article proposes a planning model for a multi-energy microgrid (MEM) that supplies the electricity, heating, and cooling loads. This controls flexible demands and provides continuous control in the presence of smart and comprehensive programming of electricity, heat, ice, compressed air, and hydrogen energy storage. The features of the MEM are considering the losses and amortization costs of electricity, heating and cooling energy storage, and the operating area of the combined heat and power (CHP) units in the planning procedure. Besides, the principle of convexity in the CHP unit operation area is attended. The proposed formulation is applicable in days of summer and winter seasons for a variety of planning studies. The outcomes represent that utilizing the proposed MEM planning results in significant advantages for the power network and the consumer. The cost savings are respectively obtained equal to 33% and 34% in the winter and summer seasons. The cost savings can be considered besides the investiture cost of MEM elements to specifying the MEM profits made during the designing step. Another valuable result is the cost-saving of PHEV smart charge about 1.38 times of PHEV smart discharge for summer and about 1.05 for winter. It also makes the curve of demand optimal utilization from the demand response program and energy storage plan. K E Y W O R D S combined heat and power (CHP), demand response, energy planning, energy storage, multienergy microgrid (MEM), plug-in hybrid electric vehicle (PHEV)

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A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building

Cited by 164 publications

References 27 publications

Scheduling a smart energy hub-based virtual power plant using benders decomposition to considering power system constraints

Scheduling a smart energy hub-based virtual power plant using benders decomposition to considering power system constraints

Mixed-integer nonlinear programming framework for combined heat and power units with nonconvex feasible operating region: Feasibility, optimality, and flexibility evaluation

Optimal planning of multi‐energy microgrid with different energy storages and demand responsive loads utilizing a technical‐economic‐environmental programming

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