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Article

Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations

1
Center for Collaborative Internet Ecosystems Research Center, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Korea
2
Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-840, Korea
*
Author to whom correspondence should be addressed.
Energies 2016, 9(6), 473; https://doi.org/10.3390/en9060473
Submission received: 19 February 2016 / Revised: 3 April 2016 / Accepted: 1 June 2016 / Published: 21 June 2016
(This article belongs to the Special Issue Microgrids 2016)

Abstract

:
We propose an optimal electric and heat energy management for a cooperative multi-microgrid community. The sequentially-coordinated operation for heat energy is proposed in order to distribute the computational burden as an extension of “Optimal Energy Management of Multi-Microgrids with Sequentially Coordinated Operations” and is following the sequentially-coordinated operations for electric energy in it. This sequentially-coordinated operation for heat energy is mathematically modeled and how to obtain the global heat energy optimization solution in the cooperative multi-microgrid community is presented. The global heat energy optimization is achieved for the cooperative community by adjusting the combined electric and heat energy production amounts of combined heat and power (CHP) generators and the heat energy production amount of heat only boilers (HOBs) which satisfy all heat loads, as well as optimize the external electric energy trading in order to minimize the unnecessary cost from the external electric trading, and/or maximize the profit from the external electric trading. To validate the proposed mathematical energy management models, a simulation study is also conducted.

1. Introduction

The concept of microgrids was proposed to make the electricity grid less centralized and provide local consumers a more reliable and cheaper electrical power supply [1]. Nowadays, heat energy becomes as important as electric energy for energy management of microgrids as combined heat and power (CHP) are commonly included in microgrids for heating and hot water services [2]. The microgrid concept can be applied to various electric grid customers, such as a university campus, a research park, a business building, an apartment complex, and/or an island. Energy management of microgrid has received tremendous interest by many researchers. One of the practical solutions for electric energy management of microgrid is multi-agent system-based operation, which has been applied in islanded mode [3,4] and in grid-connected mode [5,6,7]. This paper, however, concerns the optimal operation of energy management in multi-microgrids as defined in [8]. In this paper, we consider heat energy as well as electric energy for an optimal energy management of multi-microgrids; this paper presents sequentially-coordinated operations to manage electric and heat energy optimally for minimizing operational costs of both electric and heat energy in cooperative multi-microgrids. This paper is a heat energy extension of [9], which optimizes the electric energy management in cooperative multi-microgrids.
The optimal energy management system (EMS) has been studied for a microgrid which operates in islanded mode [10,11] or in grid-connected mode [11,12,13,14,15,16,17]. In islanded mode, when the microgrid is isolated from the power grid, an energy optimization for military forward operating base camp was solved by a dynamic programing algorithm to minimize the total daily operation cost in [10] and a resiliency-oriented microgrid optimal scheduling model is proposed to minimize the microgrid load curtailment by scheduling available resources in [11]. While the operation cost minimization problem for energy management of a microgrid has been mostly investigated, the profit maximization problem was also studied in [13]. On the other hand, an online cost minimization scheduling model for co-generation has been developed in [14]. In addition to renewable sources commonly included in a microgrid, controllable energy sources, such as CHP generators, were also considered and managed optimally by controlling their energy production amounts in [11,15,17].
Heat energy has been also considered along with electric energy in many studies of a microgrid in [18,19,20]. While the authors [19,20,21] minimized the operating cost, Bagheria and Tafreshi [18] maximized the profit from trading of electric energy by considering the operation cost. Furthermore, heat energy storage is also considered as a component of the microgrid in [19,20,21].
The energy management problem for cooperative multi-microgrids is investigated in [9,22,23], which targeted minimizing the operation cost of electric energy. For the energy management of cooperative multi-microgrids, electric energy trading was allowed not only internally between microgrids, but also externally with the power grid. Rahbar et al. [22] considered only uncontrollable electric energy sources, where the amount of production cannot be controlled for energy management purposes. On the other hand, Nguyen and Le [23] employed the scenario-based two-stage stochastic optimization approach to deal with the uncertainties of renewable energy resources and load demand in the energy scheduling problem in addition to controllable electric energy sources such as CHPs and diesel generators. Furthermore, Song et al. [9] proposed an optimal electric energy management of a cooperative multi-microgrid community with sequentially-coordinated operations in order to distribute the computational burden.
In this paper, an optimal electric and heat energy management for a cooperative multi-microgrid community is proposed. The proposed sequentially-coordinated operation for heat energy is a heat extension of [9], which is following the sequentially-coordinated operations for electric energy in [9]. The global heat energy optimization is achieved for the cooperative community by adjusting the combined electric and heat energy production amounts of CHP generators and the heat energy production amount of heat only boilers (HOBs) which satisfy all heat loads in the multi-microgrids, as well as optimize the external electric energy trading. Such adjusting of energy production amounts is performed in order to minimize the unnecessary cost from the external electric trading and/or maximize the profit from the external electric trading. A simulation study is also conducted to validate the proposed mathematical energy management models. In this paper, we did not consider electric heaters which uses electric energy for heat loads. Since electric heaters can satisfy heat loads using electric energy which can be traded externally, they can enable external heat trading by means of external electric trading. Currently, we consider electric heaters in the cooperative multi-microgrid community and are investigating an optimal energy management of the cooperative multi-microgrid community. Its results as an extension of this paper will be published in the near future.
The paper is organized as follows: first, we present a cooperative multi-microgrid community and conceptually describe the sequentially-coordinated operations of energy management for a cooperative multi-microgrid community in Section 2. Next, the mathematical model of the cooperative multi-microgrid operation process for electric energy in [9] is summarized in Section 3. Then, the sequentially-coordinated operation of heat energy optimization is mathematically modeled and how to obtain the optimal heat energy solution is presented in Section 4. Additionally, a simulation study for a cooperative multi-microgrid community with three microgrids is demonstrated in Section 5. Finally, our conclusions and future works are discussed in Section 6. Additionally, Appendices A and B explain how to find the optimization solution from the adjusted cost function in Section 4 and offers an illustrated interpretation of the optimization process for heat energy, respectively.

2. Proposed Optimal Electric and Heat Energy Management of Cooperative Multi-Microgrids

2.1. Cooperative Multi-Microgrid Community

A cooperative multi-microgrid community is composed of a group of multiple microgrids as in Figure 1 and is a cooperative operation model of electric and heat energy for a group of microgrids from an economic standpoint. Although various types of microgrids can exist according to specific configurations, a cooperative multi-microgrid community having the following configurations and features is assumed and the sequentially-coordinated operations of electric and heat energy for such a cooperative community are dealt with in this paper:
  • microgrids are equipped with photovoltaic (PV) systems, CHP generators, HOBs, and solar heat systems, but the production costs of CHP generators are different;
  • microgrids can trade electric energy not only internally with other microgrids in the cooperative community but also externally with the power grid;
  • microgrids allow only internal trading for heat energy with other microgrids in the cooperative community; this means that all heat loads should be self-supplemented by heat energy sources in the cooperative multi-microgrid community;
  • a microgrid energy management system (μEMS) manages electric energy of its microgrid; and
  • a central energy management system (central EMS) has a global optimization function to manage energy generators in multi-microgrids and to satisfy both electric and heat energy loads demanded by all multi-microgrids in the cooperative community.

2.2. Operation Process of Cooperative Multi-Microgrids

Our multi-microgrid community has two kinds of EMSs, central EMS and μEMS. A central EMS manages the electric energy globally in the microgrid, while a μEMS in a microgrid manages the electric energy locally. A central EMS and μEMSs operate cooperatively, coordinated with economic viewpoints as described in the Figure 2, and this cooperative operation process of the central EMS and μEMSs consists the following three steps:
  • Step E-1: Local optimization of electric energy in each microgrid by the μEMS;
  • Step E-2: Global electric energy trading optimization by the central EMS;
  • Step H: Global heat energy optimization by the central EMS.

3. Mathematical Modeling of Cooperative Multi-Microgrid Operation for Electric Energy [9]

In this section, the mathematical model of the cooperative multi-microgrid operation process for electric energy in [9] is summarized. Mathematical notations are first listed in Section 3.1, and the mathematical models of the operation process for electric energy are presented sequentially.

3.1. Nomenclature

Mathematical notations for electric energy are listed as follows:
  • ₩ = South Korea Won
  • t = the identifier of operation interval
  • T = the number of operation intervals
  • l = the identifier of microgrid
  • L = the number of microgrid
  • j = the identifier of HOB
  • J = the number of HOBs
  • e = the identifier of electric energy
  • C CHP l e = the electric energy production cost of the CHP in the l th microgrid (won/kWh)
  • C BUY l e ( t ) = the buying price from the power grid in the l th microgrid at t (won /kWh)
  • C SELL l e ( t ) = the selling price to the power grid in the l th microgrid at t (won /kWh)
  • C CHP l h = the heat energy production cost of the CHP in the l th microgrid (won /kWh)
  • C HOB l , j h = the cost of the j th HOB in the l th microgrid (won /kWh)
  • M LOAD l e ( t ) = electric energy demand in the l th microgrid at t (kWh)
  • M l e + ( t ) = the amount of surplus electric energy in the l th microgrid at t (kWh)
  • M l e ( t ) = the amount of short electric energy in the l th microgrid at t (kWh)
  • M PV l e ( t ) = the output produced from the PV system in the l th microgrid at t (kWh)
  • M CHP l e ( t ) = the electric energy production amount of the CHP in the l th microgrid at t (kWh)
  • M CHP l e + ( t ) = the increased electric energy production amount of the CHP in the l th microgrid at t (kWh) for the ancillary internal trading
  • M CHP l e ( t ) = the decreased electric energy production amount of the CHP in the l th microgrid at t (kWh) for the ancillary internal trading
  • M BUY l e ( t ) = the amount of the buying electric energy in the l th microgrid determined by central EMS at t (kWh)
  • M SELL l e ( t ) = the amount of the selling electric energy in the l th microgrid determined by central EMS at t (kWh)
  • M REC l e ( t ) = the received electric energy amount in the l th microgrid at t (kWh)
  • M SEND l e ( t ) = the sending electric energy amount in the l th microgrid at t (kWh)

3.2. Step E-1: Local Optimization of Electric Energy Operation Process

The cost function of a microgrid in Step E-1 is the total expense occurred by the electric energy for the microgrid when the external trading of the electric energy with the power grid is applied as follows:
C l e ( M CHP l e ( t ) ) = ( C CHP l e × M CHP l e ( t ) ) ( C SELL l e ( t ) × M l e + ( t ) ) + ( C BUY l e ( t ) × M l e ( t ) )
Step E-1 is the local optimization process of electric energy by the μEMS in each microgrid. As mentioned in [1], the local electric energy optimization function when external trading of electric energy with the power grid is applied can be expressed as follows:
M CHP l e * ( t ) = arg min  {   C l e ( M CHP l e ( t ) ) }
subjects to:
min  [ M CHP l e ] M CHP l e ( t ) max  [ M CHP l e ]
For 1 t T , 1 l L . The constraint to the objective function of a μEMS in Equation (2) implies that a CHP generator should be operated within its operational ranges.

3.3. Step E-2: Global Optimization of Electric Energy Operation Process

Step E-2 is the global optimization process of electric energy by the central EMS based on local optimization information of electric energy of each μEMS in Step E-1.
The adjusted saving cost in Step E-2 can be obtained from both main and ancillary internal trading of the electric energy between microgrids in cooperative multi-microgrids as follows:
C Elec Adj ( M SEND 1 e ( t ), , M SEND L e ( t ),  M CHP 1 e+ ( t ),,  M CHP L e+ ( t ), M CHP 1 e ( t ),,  M CHP L e ( t ) ) = ( C BUY e ( t )  C SELL e ( t ) )× l=1 L M SEND l e ( t ) +  l=1 L ( C BUY e ( t )  C CHP l e )× M CHP l e+ ( t ) +  l=1 L ( C CHP l e   C SELL e ( t ) )× M CHP l e ( t )
Then, the adjusted cost function in Step 2 can be optimized by maximizing the profit resulted by the internal trading of the electric energy as follows:
P Elec Ad j * ( t )   =  arg max  { C Elec Adj ( P Elec Adj ( t ) ) }
subjects to:
for l, such that M l e + ( t ) > 0:
M SEND l e ( t ) M l e + ( t )  when  M l e + ( t ) > 0
for l, such that M l e ( t ) > 0:
M REC l e ( t ) M l e ( t )  when  M l e ( t ) > 0
for l, such that M l e + ( t ) > 0 or M l e ( t ) > 0 :
l = 1 L M SEND l e ( t ) = l = 1 L M REC l e ( t )
for l, such that M l e + ( t ) = M l e ( t ) = 0 and l = 1 L M l e + ( t ) < l = 1 L M l e ( t ) :
M CHP l e + ( t )  max  [ M CHP l e ] M CHP l e * ( t )
l = 1 L M CHP l e + ( t ) l = 1 L M l e ( t ) l = 1 L M l e + ( t )
for l, such that M l e + ( t ) = M l e ( t ) = 0 and l = 1 L M l e + ( t ) > l = 1 L M l e ( t ) :
M CHP l e ( t ) M CHP l e * ( t )  min  [ M CHP l e ]
l = 1 L M CHP l e ( t ) l = 1 L M l e + ( t ) l = 1 L M l e ( t )
As a result of the global electric energy trading optimization, the global optimal production amount of the CHP generators located in self-sufficient microgrids have to be changed as follows:
M CHP l e * ( t ) : = M CHP l e * ( t ) + M CHP l e + ( t ) M CHP l e ( t )
for l, such that ( C SELL e ( t ) < M CHP l e ( t ) < C BUY e ( t ) ) and the buying and selling amount of electric energies to the power grid in a microgrid should be decided by trading the amount of electric energy as follows:
M BUY l e = M l e + M REC l e ( t )  when  M l e ( t ) > 0
M SELL l e = M l e + M SEND l e ( t )  when  M l e + ( t ) > 0
Finally, the total operation cost of electric energy in the cooperative multi-microgrid community satisfies all of the electric energy demand and is optimally minimized sequentially in two steps, as follows:
C TOTAL e * ( t ) = t = 1 T { l = 1 L ( C l e ( M CHP l e * ( t ) ) )   C Elec Adj ( P Elec Adj * ( t ) ) }

4. Mathematical Modeling of Cooperative Multi-Microgrid Operation for Heat Energy

In this section, the operation process of heat energy part in the microgrid energy networks (μENet) is mathematically modeled. The proposed sequentially-coordinated operation for heat energy is a heat extension of [9], which is following the sequentially-coordinated operations for electric energy in [9].
Mathematical notations are first defined in Section 4.1, and the mathematical models of the operation process are presented according to in the heat energy part operation process.

4.1. Nomenclature

Before presenting the mathematical models of the cooperative multi-microgrid operation process, mathematical notations necessary for the heat energy models are defined as follows:
  • h = the identifier of heat energy
  • η CHP l = the heat to power ratio of CHP in the l th microgrid (%)
  • M LOAD l h ( t ) = heat energy demand in the l th microgrid at t (kWh)
  • M l h + ( t ) = the amount of surplus heat energy in the l th microgrid at t (kWh)
  • M l h ( t ) = the amount of short heat energy in the l th microgrid at t (kWh)
  • M SH l h ( t ) = the output produced from the solar heat system in the l th microgrid at t (kWh)
  • M CHP l h ( t ) = the heat energy production amount of the CHP in the l th microgrid at t (kWh)
  • M CHP l h + ( t ) = the additional heat energy amount of the CHP in the l th microgrid at t (kWh)
  • M CHP l h ( t ) = the reducing heat energy amount of the CHP in the l th microgrid at t (kWh)
  • M CHP l cap = the capacity of the CHP in the l th microgrid (kWh)
  • M REC l h ( t ) = the received heat energy amount in the l th microgrid at t (kWh)
  • M SEND l h ( t ) = the sending heat energy amount in the l th microgrid at t (kWh)
  • M HOB l , j h ( t ) = the heat energy production amount of the j th HOB in the l th microgrid at t (kWh)
  • M HOB l , j cap = the capacity of the j th HOB in the l th microgrid (kWh)

4.2. Step H: Mathematical Model of Global Heat Energy Optimization

After the global electric energy optimization, the amount of heat energy from the CHP generator in a microgrid can be expressed according to the heat and electric energy ratio of the CHP as follows:
M CHP l h ( t )  =  η CHP l  ×  M CHP l e * ( t )
Then, the amount of surplus heat energy in a microgrid can be calculated as:
M l h + ( t ) : = M CHP l h ( t ) + M SH l h ( t ) M LOAD l h ( t ) ,  when  M LOAD l h ( t ) M CHP l h ( t ) + M SH l h ( t )
while the amount of heat energy shortage in a microgrid can be expressed as:
M l h ( t ) : = M LOAD l h ( t ) ( M CHP l h ( t ) + M SH l h ( t ) ) ,  when  M LOAD l h ( t ) > M CHP l h ( t ) + M SH l h ( t )
Let us define the set of the heat energy parameters as the internal trading amounts of heat energy between microgrids, the adjusted heat energy generation amounts of CHPs, and the heat energy generation amounts of HOBs to meet all heat demand in the cooperative multi-microgrid community;
P Heat Adj ( t ) =   ( M SEND 1 h ( t )   M SEND L h ( t ) ,   M REC 1 h ( t )   M REC L h ( t ) ,     M CHP 1 + h ( t ) M CHP L + h ( t ) ,
M CHP 1 h ( t ) M CHP L h ( t ) ,   M HOB 1 , 1 h ( t )   M HOB L , J h ( t ) )
The amounts of heat energy from the solar heat generators are not included since their heat energy production amounts cannot be adjusted. Then, the adjusted cost in Step H to meet all heat demand in the cooperative multi-microgrid community can be defined as the total heat production cost of HOBs, increased energy production of CHPs, and decreased energy production of CHPs as follows:
C Heat Adj ( P Heat Adj ( t ) ) = l = 1 L { j = 1 J C HOB l , j h ( t ) × M HOB l , j h ( t ) } + C CHP + Adj ( l = 1 L M CHP + h ( t ) )   C CHP Adj ( l = 1 L M CHP h ( t ) )
The second term in Equation (18) is the extra cost from the increased energy production of CHPs; the extra production cost, the profit of selling surplus electric energy resulting from increased amount of CHP electric energy production, and the savings from the decreased amount of buying electric energy is as follows:
C CHP + Adj ( l=1 L M CHP l + h ( t ) )          = l=1 L ( ( 1 η CHP l C CHP l e ( t )+ C CHP l h ( t ) )× M CHP l + h ( t ) )            C SELL e ( t )( 1 η CHP l l=1 L M CHP l + h ( t )          min[ 1 η CHP l l=1 L M CHP l + h ( t ), l=1 L M BUY l e ( t ) ] )  C BUY e ( t )          ×min[ 1 η CHP l l=1 L M CHP l + h ( t ), l=1 L M BUY l e ( t ) ]
The third term in Equation (18) is the reduced cost from the reduced energy production of CHP, which consists of the reduced production cost, the extra cost of buying electric energy due to shortage resulting from a decreased amount of CHP electric energy production, and the reduced profit from decreased selling electric energy, as follows:
C CHP Adj ( l=1 L M CHP l h ( t ) )          = l=1 L ( ( 1 η CHP l C CHP l e ( t )+ C CHP l h ( t ) )× M CHP l h ( t ) )            C BUY e ( t )( 1 η CHP l l=1 L M CHP l h ( t )          min[ 1 η CHP l l=1 L M CHP l h ( t ), l=1 L M SELL l e ( t ) ] )  C SELL e ( t )          ×min[ 1 η CHP l l=1 L M CHP l h ( t ), l=1 L M SELL l e ( t ) ]
Note that both the second term and the third term in Equation (18) cannot exist at the same time. Then, the globally-optimized adjusted production amounts of heat energy in Step H can be obtained, as follows:
P Heat Adj * ( t ) =  arg min  { C Heat Adj ( P Heat Adj ( t ) ) }
subject to:
M LOAD l h ( t ) M SH l h ( t ) + M CHP l h ( t ) + M CHP l + h ( t ) M CHP l h ( t ) +   M REC l h ( t ) M SEND l h ( t ) + M HOB l , j h ( t )
M CHP l + h ( t )   max   [ M CHP l h ] M CHP l h ( t )
M CHP l h ( t ) M CHP l h ( t ) min [ M CHP l h ]
M HOB l , j h ( t ) M HOB l , j cap ,   1 j J l
M SEND l h ( t )     M CHP l h + ( t ) + M CHP l + h ( t ) M CHP l h ( t ) + j = 1 J   M HOB l , j h ( t )
l = 1 L M SEND l h ( t ) = l = 1 L M REC l h ( t )
for 1 l L , 1 t T. The first constraint to the global heat energy optimization in Equation (22) imposes that the heat demand in a microgrid has to be satisfied. Inequality in Equation (22) allows heat energy to be produced more than needed so that the total cost of both electric and heat energy can be minimized by adjusting external electric energy trading amounts while wasting heat energy. The constraints in Equations (23) and (24) are applied to the CHPs, while the constraints in Equation (25) are to HOBs. The constraints on the internal trading amounts of heat energy between microgrids are expressed in Equations (26) and (27).
Since the adjusted cost function in Step H has a min() function, it has to be linearized to find the global heat energy optimization solution as in Appendix A; first the linearized adjusted cost function has to be optimized by CPLEX for each case, and then the global heat energy optimization solution has to be selected as the optimization solution for the case which results in the minimum adjusted cost among the five cases, as in Appendix A. Please refer to Appendix B, which gives an illustrated interpretation of the heat energy optimization process for typical cases.
After the global heat energy optimization is completed, the external trading amount of electric energy with the main grid has be re-arranged again, as follows:
when l = 1 L M SELL l e ( t ) > 0:
l = 1 L M SELL l e ( t )   : = l = 1 L M SELL l e ( t ) + 1 η CHP l l = 1 L M CHP l + h ( t )
for 1 η CHP l l = 1 L M CHP l + h ( t ) 0 :
l = 1 L M SELL l e ( t )   : =   l = 1 L M SELL l e ( t )   1 η CHP l l = 1 L M CHP l h ( t )
for 1 η CHP l l = 1 L M CHP l h ( t ) M SELL e ( t ) when l = 1 L M CHP l h ( t ) > 0 :
l = 1 L M BUY l e ( t )   : =   1 η CHP l l = 1 L M CHP l h ( t ) l = 1 L M SELL l e ( t ) ,  and  l = 1 L M SELL l e ( t )   : = 0
for 1 η CHP l l = 1 L M CHP l h ( t ) > l = 1 L M SELL l e ( t ) when l = 1 L M CHP l h ( t ) > 0
and when l = 1 L M BUY l e ( t ) > 0:
l = 1 L M BUY l e ( t )   : =   l = 1 L M BUY l e ( t ) +   1 η CHP l l = 1 L M CHP l h ( t )
for l = 1 L M CHP l h ( t ) > 0 :
l = 1 L M BUY l e ( t )   : =   l = 1 L M BUY l e ( t ) 1 η CHP l l = 1 L M CHP l + h ( t )
for 1 η CHP l l = 1 L M CHP l + h ( t )   l = 1 L M BUY l e ( t ) when l = 1 L M CHP l + h ( t ) > 0 :
l = 1 L M SELL l e ( t )   : =   1 η CHP l l = 1 L M CHP l + h ( t ) l = 1 L M BUY l e ( t )  and  l = 1 L M BUY l e ( t ) = 0
for 1 η CHP l l = 1 L M CHP l + h ( t ) > l = 1 L M BUY l e ( t ) when l = 1 L M CHP l + h ( t ) > 0 .
Furthermore, the total heat energy produced by the CHP generator in a microgrid can be re-arranged, as follows:
M CHP l h * ( t )   : = M CHP l h ( t )   + M CHP l + h * ( t )  when  M CHP l + h * ( t ) > 0
M CHP l h * ( t )   : = M CHP l h ( t ) M CHP l h * ( t )  when  M CHP l h * ( t ) > 0

4.3. Total Operation Costs

Finally, the total optimum operation cost can be expressed with the objective functions defined earlier, as follows:
C TOTAL * ( t ) =   l = 1 L ( C l e ( M CHP l e * ( t ) ) +   C CHP l h ( t ) × M CHP l h * ( t ) )   C Elec Adj ( P Elec Adj * ( t ) ) + C Heat Adj ( P Heat Adj * ( t ) )
The total operation cost of the cooperative multi-microgrid for electric energy and heat energy can be reduced significantly by performing all of the energy optimization processes sequentially in the three steps as shown in Section 3 and Section 4.

5. Simulation Study

A simulation study has been conducted for a cooperative multi-microgrid community to show the optimal electric and heat energy management with sequential operation processes and its results, especially for the global heat energy optimization, are presented in this section.
In our simulation study, a cooperative multi-microgrid community is composed of three microgrids having different CHPs and HOBs. Note that when a CHP produces 1 kWh electric energy, η CHP l kWh heat energy is produced; the unit production cost of combined electric and heat energy of a CHP can be defined as the combined production cost of 1 kWh electric energy and η CHP l kWh heat energy; that is, ( C CHP l e ( t ) + η CHP l C CHP l h ( t ) ) as shown in Table 1. For simplicity, we assume that C CHP l e ( t ) = C CHP l h ( t ) . The production costs ( C HOB l h ( t ) ) of HOB A, B, and C are 240, 230, and 240, respectively.
The external trading prices of electric energy are designed as time of use (TOU) plan having off-peak, non-peak, and peak hours for 24 h of a day as in Table 2; the buying price is always set higher than the selling price. The combined E and H production costs of CHPs are compared to external trading prices by the TOU plan in Figure 3.
The simulation results for the cooperative multi-microgrids are arranged in Table 3, Table 4 and Table 5 for Steps E-1, E-2, and H, respectively. First, the local and global optimal operation results of electric energy from Steps E-1 and E-2 are arranged in Table 3 and Table 4. Since the heat energy optimization process is the main focus of this paper, electric energy optimization results in Table 3 and Table 4 will not be discussed here (please refer [9] for a better understanding of electric energy optimization process).
First, Case_1 ( l = 1 L M CHP l + h ( t ) = l = 1 L M CHP l h ( t ) = 0 ) occurs for Time = 8. Since all three CHPs already produce their maximum capacities in Step E-2 and there is still a heat energy shortage, this heat energy shortage is supplemented by the heat energy produced from HOB B in Step H. Since the production cost of HOB B is lower than other HOBs, and higher than unit production costs of combined E and H energy of all CHPs, only HOB B produces 113 kWh heat energy to fulfill the heat energy shortage in Microgrid A and, thus, achieve global heat energy optimization in Step H. The energy shortage in Microgrid A (161 kWh) is supplemented by receiving 141 kWh heat energy from Microgrid B and 20 kWh heat energy from Microgrid C.
Now, Case_2 ( l = 1 L M CHP l + h ( t ) > 0 and l = 1 L M CHP l h ( t ) = 0 ) occurs for Time = 1–5. CHP A for Time = 1–4 increases its production but the heat energy shortage in Microgrid A is supplemented by other CHPs, while CHP B for Time = 5 and CHP C for Time = 4 also works similarly to Example-1 in Figure B1. On the other hand, CHP B for Time = 1–5 increases its production and its surplus heat energy is sent to other microgrids while CHP C for Time = 1–4 also works similarly just like Example-2 in Figure B2.
Finally, Case_3 ( l = 1 L M CHP l + h ( t ) = 0 and l = 1 L M CHP l h ( t ) > 0 ) occurs for Time = 6, 7, 9–24. CHP C for Time = 7, 9–11, 14, 15, 17, 22–23 decreases its production and the heat energy shortage in Microgrid C is supplemented by other CHPs; CHP B for Time = 18, 22 also works similarly to Example-3 in Figure B3. Just like Example-4 in Figure B4, all three CHPs for Time = 24 reduce their production and, yet, have heat energy wasted. Similarly, CHP B for Time = 12, 13, 19, and CHP C for Time = 19–21 also waste heat energy even after reducing energy production of the CHP. For Time = 12 and 13, CHP A produces its maximum energy since its unit production cost of combined E and H energy is lower than the selling price of electric energy; CHP B produces the amount of energy just enough not to buy or sell any electric energy since its unit production cost of combined E and H energy is between the buying and selling prices of electric energy; and CHP C produces its minimum energy since its unit production cost of combined E and H energy is higher than the buying price of electric energy. Note the simulation results for Time = 12 and 13: the total decreased amount of electric energy in Step H is the same as the total selling amount of electric energy after global electric optimization in Step E-2.

6. Conclusions

In this paper, we considered heat energy in addition to electric energy for a cooperative multi-microgrid community and studied an optimal energy management problem with sequentially-coordinated operations to satisfy electric loads, as well as heat loads. The sequentially-coordinated operation for heat energy in this paper is following the sequentially-coordinated operations for electric energy in [9] and, thus, is a heat energy extension of [9]. First, we modeled this sequentially-coordinated operation for heat energy mathematically and presented how to obtain the global heat energy optimization solution in the cooperative multi-microgrid community. The global heat energy optimization is achieved for the cooperative community by adjusting the combined electric and heat energy production amounts of CHP generators and the heat energy production amount of HOBs; these adjusted energy production amounts satisfy all heat loads in the multi-microgrids, as well as optimize the external electric energy trading in order to minimize the unnecessary cost from the external electric trading and/or maximize the profit from the external electric trading.
As a further study, we are now considering electric heaters in this cooperative multi-microgrid community with sequentially-coordinated operations to investigate external heat trading through electric heaters, which are running by electric energy form the main grid. Its interesting result, as an extension of this paper, will be published in the near future.

Acknowledgments

This work was supported by the Power Generation & Electricity Delivery Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea. (No. 20141020402350)

Author Contributions

The paper was a collaborative effort between the authors. The authors contributed collectively to the theoretical analysis, modeling, simulation, and manuscript preparation.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Linearization of the Adjusted Cost Function in Step H

The adjusted Equation (18) of Step H is as follows:
C Heat Adj ( P Heat Adj ( t ) ) =   l = 1 L { j = 1 J ( C HO B l , j h ( t ) × M HO B l , j h ( t ) ) }   + C CH P + Adj ( l = 1 L M CH P l + h ( t ) ) C CH P + Adj ( l = 1 L M CH P l h ( t ) )
since the last two terms in Equation (18) have a min() function as expressed in Equations (19) and (20), CPLEX (IBM ILOG) cannot be utilized directly to find the optimization solution of the adjusted cost function for heat energy extension in Step H.
In Appendix A, the adjusted cost function in Step H will be linearized by removing min() in it depending on the conditions for l = 1 L 1 η CHP l M CHP l + h ( t ) and l = 1 L 1 η CHP l M CHP l h ( t ) . This linearization process of the adjusted cost function in Step H enables us to utilize CPLEX and, thus, find the global heat optimization solution.
First, let us consider when CHPs do not change their production amounts in Step H, which implies as follows:
1 η CHP l l = 1 L M CHP l + h ( t ) = 0  and  1 η CHP l l = 1 L M CHP l h ( t ) = 0
Thus, the adjusted cost function in Step H includes only the total heat production cost of HOBs as follows:
Case _ 1 :   C Heat Adj ( P Heat Adj ( t ) ) =   l = 1 L { j = 1 J ( C HOB l , j h ( t ) × M HOB l , j h ( t ) ) }
Secondly, let us consider when CHPs increase energy production in Step H, which implies as follows:
l = 1 L M CHP l + h ( t ) > 0  and  l = 1 L M CHP l h ( t ) = 0
In this situation, the following two cases have to be considered due to the min() function in Equation (19);
Case _ 2 - 1 :   0 < 1 η CHP l l = 1 L M CHP l + h ( t ) l = 1 L M BUY l e ( t )
Case _ 2 - 2 :   1 η CHP l l = 1 L M CHP l + h ( t ) > l = 1 L M BUY l e ( t )
Then, the adjusted cost functions in Step H for the above two cases become as follows:
Case _ 2 - 1 :   C Heat Adj ( P Heat Adj ( t ) ) =   l = 1 L { j = 1 J ( C HOB l , j h ( t ) × M HOB l , j h ( t ) ) } + l = 1 L ( ( 1 η CHP l C CHP l e ( t ) + C CHP l h ( t ) ) × M CHP l + h ( t ) )   C BUY e ( t ) × l = 1 L 1 η CHP l M CHP l + h ( t )
Case _ 2 - 2 :   C Heat Adj ( P Heat Adj ( t ) ) = l = 1 L { j = 1 J ( C HOB l , j h ( t ) × M HOB l , j h ( t ) ) } + l = 1 L (   ( 1 η CHP l C CHP l e ( t )   + C CHP l h ( t ) ) × M CHP l + h ( t ) ) C SELL e ( t ) ( l = 1 L 1 η CHP l M CHP l + h ( t ) l = 1 L M BUY l e ( t )   )     C BUY e ( t ) × l = 1 L M BUY l e ( t )
Finally, let us consider the situation when CHPs decrease energy production in Step H, which implies as follows:
l = 1 L M CHP l + h ( t ) = 0  and  l = 1 L M CHP l h ( t ) > 0
In this situation, there are following two cases due to the min() function in Equation (20);
Case _ 3 - 1 :   0 < 1 η CHP l l = 1 L M CHP l h ( t ) l = 1 L M SELL l e ( t )
Case _ 3 - 2 :   1 η CHP l l = 1 L M CHP l h ( t ) > l = 1 L M SELL l e ( t )
Then, the adjusted cost functions in Step H for the above two cases become as follows:
Case _ 3 - 1 :   C Heat Adj ( P Heat Adj ( t ) ) =   l = 1 L { j = 1 J ( C HOB l , j h ( t ) × M HOB l , j h ( t ) ) } l=1 L ( ( 1 η CHP l C CHP l e ( t ) + C CHP l h ( t ) ) × M CHP l h ( t ) )   +   C SELL e ( t ) × l=1 L 1 η CHP l M CHP l h ( t )
Case _ 3 - 2 :   C Heat Adj ( P Heat Adj ( t ) )=  l=1 L { j=1 J ( C HOB l,j h ( t )×( t ) ) }  l=1 L ( ( 1 η CHP l C CHP l e ( t )+ C CHP l h ( t ) )× M CHP l h ( t ) ) +  C BUY e ( t )( l=1 L 1 η CHP l M CHP l h ( t ) l=1 L M SELL l e ( t ) )+  C SELL e ( t )× l=1 L M SELL l e ( t )

Appendix B. Illustrated Interpretation of Optimization Operation for Heat Energy

For Case_2-1, the increased production amount of electric energy in Step H ( 1 η CHP l l = 1 L M CHP l + h ( t ) ) cuts off the electric energy purchase in Step E-2 if there is electric energy purchase ( l = 1 L M BUY l e ( t ) > 0 ) due to an electric energy shortage. In such a case, it will be sold to the main grid ( l = 1 L 1 η CHP l M CHP l + h ( t ) l = 1 L M BUY l e ( t ) ) .
On the other hand, the heat energy shortage in a microgrid is supplemented, first, by the increased heat energy of its CHP generator, and then by the received heat energy from other microgrids with surplus heat energy, as in Figure B1. However, even when there is a heat energy surplus in a microgrid, the microgrid can increase its CHP production and sends its surplus heat energy to other microgrids as in Figure B2.
Figure B1. Example-1 when l=1 L M CHP l + h ( t )>0 .
Figure B1. Example-1 when l=1 L M CHP l + h ( t )>0 .
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Figure B2. Example-2 when l=1 L M CHP l + h ( t )>0 .
Figure B2. Example-2 when l=1 L M CHP l + h ( t )>0 .
Energies 09 00473 g005
For Case_3-1 and Case_3-2, the decreased production amount ( 1 η CHP l l = 1 L M CHP l h ( t ) ) of electric energy in Step H first cuts off the electric energy selling in Step E-2 if l = 1 L M SELL l e ( t ) > 0 and then can be supplemented by new electric energy purchase ( l = 1 L 1 η CHP l M CHP l h ( t ) l = 1 L M SELL l e ( t ) ) .
On the other hand, the heat energy shortage in a microgrid is supplemented by the received heat energy from other microgrids with surplus heat energy, as in Figure B3. However, the surplus heat energy can be wasted even after internal heat trading, as in Figure B4. Such heat wasting can happen when the buying price of electric energy is higher than the unit combined E and H production price of a CHP, since producing electric and heat energy by the CHP would save money instead of buying electric energy even though the produced heat is wasted. Furthermore, when the selling price of electric energy is higher than the unit combined E and H production price of a CHP, the CHP has to produce its maximum electric and heat energy since selling electric energy produced by the CHP is profitable even after the produced heat energy is wasted.
Figure B3. Example-3 when l=1 L M CHP l h ( t )>0 .
Figure B3. Example-3 when l=1 L M CHP l h ( t )>0 .
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Figure B4. Example-4 when l=1 L M CHP l h ( t )>0 .
Figure B4. Example-4 when l=1 L M CHP l h ( t )>0 .
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Figure 1. Information and energy flows in cooperative multi-microgrid community. EMS: energy management system; CHP: combined heat and power.
Figure 1. Information and energy flows in cooperative multi-microgrid community. EMS: energy management system; CHP: combined heat and power.
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Figure 2. Operation process of the cooperative multi-microgrid community.
Figure 2. Operation process of the cooperative multi-microgrid community.
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Figure 3. Unit production cost of combined E and H energy of CHPs.
Figure 3. Unit production cost of combined E and H energy of CHPs.
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Table 1. Combined electric and heat (E and H) energy production cost of CHPs.
Table 1. Combined electric and heat (E and H) energy production cost of CHPs.
CharacteristicsCHP ACHP BCHP C
Combined electric and heat (E and H) energy90120165
1 kWh Electric energy ( C CHP l e ( t ) ) 42.8653.3366
η CHP l kWh Heat energy ( C CHP l h ( t ) ) 47.1466.6799
Heat and power ratio ( η CHP l ) 1.11.251.5
Table 2. External trading prices by time of use (TOU) plan.
Table 2. External trading prices by time of use (TOU) plan.
PriceOff-PeakNon-PeakPeak
Buying price57105130
Selling price4785110
Table 3. Local optimization of electric energy in Step E-1.
Table 3. Local optimization of electric energy in Step E-1.
TMicrogrid AMicrogrid BMicrogrid C
M L O A D l e M C H P l e M P V l e M l e M l e + M L O A D l e M C H P l e M P V l e M l e M l e + M L O A D l e M C H P l e M P V l e M l e M l e +
13694500081192360001685504800700
234545000105187360001735254800450
338245000684024020005754800950
435145000993303600030472480008
53814500069399399000485480050
637245000783723720004954800150
7350450001001776000042353070000170
8336450601201656000043549270070215
9371450908814360000457497700100213
103874501007321260050393467700120245
113934501307020160080407497700160219
124284501804031760010029379370025680
13417450230562996001503167237002805
144144502506124760019037266470024060
1540045024074216600200404604700200116
163514502101206036001401180770013940
17357450180111600600120127697004650
183564508010265260044806017000099
19347450001034366000016455870000142
204674500170423600001777197000190
214324500018532600006853370000167
22416450003465160005107297000290
2335745000936006000007697000690
244004500050216600003846047000096
Table 4. Global optimization of electric energy in Step E-2.
Table 4. Global optimization of electric energy in Step E-2.
TMicrogrid AMicrogrid BMicrogrid C
M C H P l + e M C H P l e M S E N D l e M R E C l e M B U Y l e M S E L L l e M C H P l + e M C H P l e M S E N D l e M R E C l e M B U Y l e M S E L L l e M C H P l + e M C H P l e M S E N D l e M R E C l e M B U Y l e M S E L L l e
1002300580007000004700120
2001700880004500002800144
30068000000950027027000
400000990000080000030
50044002500050003903900
600270051000150001201200
7000001000000017000000423
8000001200000021500000435
900000880000021300000457
1000000730000024500000393
1100000700000021900000407
1200800320006800006000233
13000005600000500000316
140000061000006000000372
1500000740000011600000404
16008600340009400008003
17005900520006500006006
1800240078002300750004800
19000001030000014200000164
2000017000001900003600141
210000018000001670000068
22003400000012000002100
23006900240006900000000
240000050000009600000384
Table 5. Global optimization of heat energy in Step H.
Table 5. Global optimization of heat energy in Step H.
TMicrogrid A
M L O A D l e M L O A D l h M P V l e M S H l h M C H P l e M C H P l h M C H P l + e M C H P l e M C H P l + h M C H P l h M H O B l h M S E N D l h M R E C l h M W A S l h
1369778004504950000002830
2345641004504950000001460
338259000450495000000950
435156600450495000000710
538145500450495000004000
63723960035939509101000010
7350641004504950000001460
8336656604504950000001610
937153890450495000000430
10387540105450495000000400
11393474137450495000002800
1242837018104504950000063072
1341741223154504950000066032
144144932518450495000002000
154005322416450495000000210
16351512211445049500000030
17357532189450495000000280
183563268045049500000100069
19347301004504950000000194
20467240004504950000060249
2143241000450495000000085
22416337004504950000015800
2335747000450495000002500
244003680038041807007700050
TMicrogrid B
M L O A D l e M L O A D l h M P V l e M S H l h M C H P l e M C H P l h M C H P l + e M C H P l e M C H P l + h M C H P l h M H O B l h M S E N D l h M R E C l h M W A S l h
1192748006007502400300010110300
21877320060075024003000628000
3402715006007501710213.7003500
43306490060075024003000010100
53994900038047520025000150
637243000360450000002000
7177532006007500000021800
816572200600750000011314100
9143649056007500000010600
10212620586007500000013800
112016178126007500000014500
123175211015555.1693.8044.9056.2000187.8
132995361518443553.701570196.200035.8
142475501920466.45830133.6016705300
152165672016568.8711031.2039016000
16603767141360075000000040
176007191210600750000004100
186526714836045002400300002130
19436430003604500240030000020
2042345600360450024003000060
215326040036045002400300001540
2265169200462.45780137.60172001140
236006190053667006408005100
24216420003604500240030000030
TMicrogrid C
M L O A D l e M L O A D l h M P V l e M S H l h M C H P l e M C H P l h M C H P l + e M C H P l e M C H P l + h M C H P l h M H O B l h M S E N D l h M R E C l h M W A S l h
155087000700105022003300018000
25259840070010502200330006600
3575930006609901800270006000
447210800070010502200330000300
548574500480720000000250
649573900480720000000190
753098400608912092013800720
84921030707001050000002000
94971080100678101702203300630
10467996120598.78980101.3015200980
11497100516455282801480222001730
127937892564807200220033000630
137237942884807200220033000660
1466480324104807200220033000730
15604870201148072002200330001390
168077801313516774018402760700
1776989049578.78680121.3018200130
18601612054807200220033002131000
195586100048072002200330000110
20719702004807200220033000018
2153348300480720022003300154083
22729764004807200220033000440
23769796004807200220033000760
24604700004807200220033000020

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Song, N.-O.; Lee, J.-H.; Kim, H.-M. Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations. Energies 2016, 9, 473. https://doi.org/10.3390/en9060473

AMA Style

Song N-O, Lee J-H, Kim H-M. Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations. Energies. 2016; 9(6):473. https://doi.org/10.3390/en9060473

Chicago/Turabian Style

Song, Nah-Oak, Ji-Hye Lee, and Hak-Man Kim. 2016. "Optimal Electric and Heat Energy Management of Multi-Microgrids with Sequentially-Coordinated Operations" Energies 9, no. 6: 473. https://doi.org/10.3390/en9060473

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