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Global Energy Interconnection
Volume 1, Issue 2, Apr 2018, Pages 108-114
Economic dispatch constrained by central multi-period security for Global Energy Interconnection and its application in the Northeast Asia
Abstract
In recent years, the global energy interconnection (GEI) has more and more profound influence around the world,which is a highly practical way for humans to handle the energy crisis. In the studies of GEI, the economic dispatch (ED)is a basic and important content. In this paper, a model of dynamic economic dispatch (DED) of GEI is presented, which include the renewable energy generation. The objective function of this model is composed of the operating costs and the renewable energy curtailment. A series of case studies for the transnational energy interconnection in Northeast Asia are given to verify the superiority of GEI and for further analysis.
1 Introduction
During the almost three hundred years of industrialized process, a huge number of fossil energy has been exploited and utilized, which gave a profound promotion to development of the global economy and human society.However, the problems are more and more prominent that the nonrenewable fossil energy is nearly exhausted, along with the phenomenon of environmental pollution and climate change. Therefore, it is obvious that human society can hardly survive with the traditional method of energy utilization, and the energy revolution is extremely urgent[1-4].
One important part of the energy revolution is the widely using of renewable energy resources, for example,wind energy and solar energy. The renewable energy resources have unexhausted reserves all over the world and are friendly to the environment, which could satisfy the increasing energy demand of human society. Nevertheless,the allocation of renewable energy resources is pretty unbalance among countries and regions, for example,there are abundant wind energy resources in the Arctic,which has few energy demands. Moreover, such a natural distribution is unchangeable, which cause more challenges to the optimal utilization of renewable energy resources [5].
Based on the background above, the concept of “global energy interconnection (GEI)” has been proposed, which has aroused more and more attention around the world.The GEI aims at developing a global power grid, which can transmit the electrical power converted from renewable energy resources and other forms of energy all over the world, become the vital hub of the energy allocation optimization, and promote the smooth progress of energy revolution. The significant features of GEI mainly include[6]:
1) Extensively interconnected. This is the most fundamental feature of GEI, which has plentiful meaning.From microgrids to regional distribution networks,intracontinental power grids to intercontinental power grids, every part no matter huge or small is connected closely and develops coordinately, making a complete system of GEI.
2) Strong and Smart. The power grids are the most complex dynamical system, and GEI is the highest form.The flexible and stable operation, as well as the robust adaptation and self-healing capability of GEI, both need the most advanced techniques to support and make the GEI strong and smart enough.
3) Open and interactive. The well cooperation of countries is of great necessity for the GEI. Thus, the construction and operation of GEI must be open and equal for each country. In addition, the load side should also participate actively in the GEI to realize the two-way interaction between the grid side and load side.
Among the studies of GEI, economic dispatch (ED) is a basic and vital content. Generally speaking, the ED is an optimization problem aims to minimize the operation cost of power system while satisfying various constraints. From the view of time scale, the ED problem can be divided into two kinds: static economic dispatch (SED) [7], [8] and dynamic economic dispatch (DED) [9-11]. The SED only considers the ED problem with one single time period,i.e. the connections among different time periods are omitted. Oppositely, the DED fully considers the coupling relationship of different time periods, for example, the ramp limits of units. Despite that the DED is more complex, it can better reflect the reality of system operation, and get more practical results [12]. In the GEI, the penetration of renewable energy generation is large, which bring more volatility to the system and make a closer connection of time periods. If SED is applied to the GEI, probably the dispatching results will be infeasible. Thus, DED is a better choice for GEI and used in this paper.
As it is mentioned above, the ED is an optimization problem which has its objective function. In the traditional ED, the objective function mainly consists of the fuel costs of thermal units. However, this cannot meet the various requirements of GEI, for instance, the sustainability.Thus, multi-objective function [13], [14] should be introduced into the ED of GEI. One common method to handle the objective functions with different dimension is distributing certain weight coefficients to them and adding components into one single objective function. In this paper, the curtailment of renewable energy generation is put into the objective function to balance the economy and sustainability.
The rest of this paper is organized as follows. Section 2 gives the model of DED for GEI, which including the parts of renewable energy generation. Section 3 presents the case studies of the application on the transnational energy interconnection of Northeast Asia, and the conclusion is followed in Section 4.
2 Problem formulations
Fig. 1 shows the diagram of economic dispatch for global energy interconnection. In each country, there are thermal units, renewable energy generation and load,which are connected as a national power system through transmission lines. Between the countries, there are the tielines to transmit electrical power and exchange dispatching information, which realize the interconnection of national power systems. The optimization problem of DED for GEI is formulated as follows.
Fig. 1 Diagram of economic dispatch for global energy interconnection
2.1 Objective function
The objective function of DED for GEI is divided into two parts. The first part is the same as traditional ED, which is composed of the operating costs of thermal units. The fundamental requirement of power systems, i.e.the economic efficiency, is reflected in the first part. The second part mainly considers the sustainable character,which consists of the renewable energy curtailment. The objective function is given as:
In fact, the weight coefficient ωp can be fixed asω p=1,and the other two weight coefficients change according to proportion, which can reduce the number of parameters and guarantee obtaining the same results. The objective function is rewritten as:
where ρw andρs are the proportionally changed weight coefficients of wind power curtailment and photovoltaic power curtailment. The two terms withρwand ρshave clear meanings, which can be considered as penalty terms to balance choice tendency between economy and sustainability.
2.2 Constraints
1) Power balance equation
2) Output bounds of thermal units
3) Output bounds of wind farms and photovoltaic plants
4) Ramp limits of thermal units
5) Maximum transmission capacity of lines and tie-lines
The outputs of wind farms and photovoltaic plants are considered with enough flexibility, which can be arbitrarily controlled within the maximum range. Thus, there is no ramp limit of wind farms and photovoltaic plants. In addition, the permitted transmission capacity of tie-lines not only depends on the electrical characteristics, but also the agreement between the countries.
3 Case studies
The development of GEI is planned as three steps:intracontinental interconnection, intercontinental interconnection, and global interconnection. Nowadays, the GEI is in the early stage, and the transnational energy interconnections are in the ascendant, among which the Northeast Asia plays an essential role.
Fig. 2 gives the simulation framework of the transnational energy interconnection in Northeast Asia. As shown in the figure, there are mainly five countries and regions included in the Northeast Asia: Mongolia, North and Northeast China, North Korea, South Korea and Japan.Broadly speaking, Mongolia and North and Northeast China are major wind power and solar power bases, and North and Northeast China, South Korea, and Japan are main load centers. In this case, 80 nodes are constructed according to the partition of small region power grids in China and geographical position relationships in other countries, with 9 tie-lines combining these countries. The time periods studied totally is 168 hours in a week. In addition, the countries are located in different time zones,and a time standard (Beijing time in this case) need be chosen for time conversion.
Fig. 2 Transnational energy interconnection of Northeast Asia
Table 1 Dispatching results of isolated and connected operation
Operation mode Total curtailment rate Total cost(108¥)Wind Photovoltaic Isolated 15.33% 24.23% 4.3489 Connected 0.00% 0.00% 2.6580
Assume the penalty coefficients areρ w =ρs = 50, and the capacities of transmission lines and tie lines are large enough, i.e. there is no line blocking problem. Solve the isolated model without tie-lines and the connected model with tie-lines respectively, and the dispatching results are shown in Table 1. Obviously, the connected mode has great superiority compared with the isolated mode, which both decreases the renewable energy generation curtailment rates and saves lots of operation costs. Under the isolated operation mode, for the renewable energy bases like Mongolia, the permitted wind power and photovoltaic power are far larger than the demand, and these clean energies can only be curtailed without tie-lines; for the load center like Japan, the outputs of thermal units have to increase to meet the load requirement. Thus, it is verified that the GEI is highly beneficial to the economy and sustainability of human society.
Fig. 3 Total energy transmission in Northeast Asia (TWh)
Furthermore, the total energy transmission results of the connected mode are presented in Fig. 3. It can be concluded that the power flow direction is from the renewable energy bases to the load centers, which realizes the energy complementary and optimal allocation. Moreover, the forecasted maximum electrical energy from wind and photovoltaic resources in Mongolia is calculated as 3.58 TWh, which is just a little larger than the sending-out electrical energy (3.40 TWh). That is to say, the renewable energy resources in Mongolia are abundant but the loads are light, which accords with the characters of power system in Mongolia.
Table 2 Dispatching results with tie-line faults
C=China, M=Mongolia, N=North Korea, S=South Korea, J=Japan
Tie-lines faults location Total curtailment rate Total cost(108¥)Wind Photovoltaic None 0.00% 0.00% 2.6580 C-M 14.81% 24.74% 2.8758 C-N 0.00% 0.00% 2.6580 C-S 0.00% 0.00% 2.6580 N-S 0.00% 0.00% 2.6580 S-J 0.00% 0.00% 3.2094
There might be tie-lines faults between two countries for various reasons, such as political factors and natural disasters. Table 2 gives the dispatching results when the tie-lines faults occur between some two countries. When the tie-lines faults occur between China and Mongolia,the renewable energy generation curtailment rate rise up rapidly, and the total cost also increases. When the tie-lines faults occur between South Korea and Japan, the total cost rises up greatly. However, because there is a loop network among China, North Korea, and South Korea, as for other tie-lines faults, the dispatching results remain unchanged.Therefore, more loop networks in the GEI can improve its reliability and security.
Generally speaking, the renewable energy resources and load demands have obvious seasonal characteristics.For the wind energy, because of the monsoon climate in the Northeast Asia, the average wind speed is larger in spring and winter than that in summer and autumn. For the photovoltaic energy, which is mainly influenced by the solar light intensity, it rises up to the maximum in summer and falls down to the minimum in winter, which gets a medium value in spring and autumn. For the load demand,the peaks appear in summer and winter with the reason of cooling and heating supplies. Base on the analysis above,the cases of four different seasons are constructed and the results are shown in Table 3.
Table 3 Dispatching results of renewable energy generation in different seasons
W=Wind, P=Photovoltaic, S=Summary
Season Generation energy (TWh) Generation percentage W P S W P S Spring 10.17 8.04 18.21 14.26% 11.28% 25.54%Summer 7.82 12.06 19.88 7.84% 12.08% 19.92%Autumn 7.82 8.04 15.86 10.97% 11.28% 22.25%Winter 11.74 4.02 15.76 13.71% 4.70% 18.41%
As it is presented in Table 3, the total generation energy of wind power and photovoltaic power is larger in spring and summer, which is smaller in autumn and winter. However, the generation percentage shows different feature, which is larger in spring and autumn,while smaller in summer and winter. This is a result from the seasonal fluctuation of load demand. Thus, these two statistical standards of renewable energy generation should both be considered in practice to obtain a more reasonable evaluation. Moreover, it can be observed that the wind power and photovoltaic power have complementarity to some degree, which is beneficial for the stable operation of power systems. For example, from autumn to winter, the wind power rises up yet the photovoltaic power goes down,but their summary almost maintains unchanged. Therefore,it is important to develop the wind farms and photovoltaic plants coordinately in the GEI.
Table 4 Dispatching results with different wind power penalty coefficients
Wind power penalty coefficient pw Total cost(108¥)0 12.11% 3.0304 50 11.27% 3.0377 100 10.89% 3.0489 500 10.49% 3.0805 1000 10.46% 3.0901 Wind power curtailment rate
Table 4 gives the dispatching results with different wind power penalty coefficient in the objective function. In order to highlight the influence of pw , the outputs of photovoltaic plants are assumed as zero, the forecasted outputs of wind farms are reconstructed with greater volatility, and the maximum ramp rate of thermal units are decreased to 15%of the capacity per hour. It can be observed that when pw increases, the wind power curtailment rate is reduced but the total cost of the system gets larger. This is because that for the better accommodation of wind power, the thermal units have to change the operation mode to obtain more total ramping ability, which goes against to the economy.In conclusion, these results validate that the economic efficiency and sustainable capability are often opposite, and pw reflects the selection preference between them. Similar analysis can be put onto ps and the conclusion goes the same.
4 Conclusions
This paper mainly proposes a dynamic economic dispatch model for the GEI, and the renewable energy generations of wind power and photovoltaic power are consider in it. The case studies which apply the model to the transnational energy interconnection of Northeast Asia validate the huge benefits of GEI. Further conclusions from the case studies are:
1) More loop networks among countries in the GEI can improve its reliability and security, especially when the tielines faults occur;
2) It is beneficial to develop the wind farms and photovoltaic plants coordinately in the GEI, which can help the stable operation of power systems;
3) The penalty coefficients of renewable energy generation curtailment reflect the selection preference between economy and sustainability, which should be chosen properly according to the reality. Specifically, when economy is preferred, the penalty coefficients should be small; on the contrary, when sustainability weighs more,the penalty coefficients should be large.
Acknowledgements
This work was supported in part by National Key Research and Development Program of China(2016YFB0901900), in part by the Science and Technology Project of SGCC-Research on Grid Dispatching and Transaction Mode for Global Energy Interconnection, in part by China Postdoctoral Science Foundation(2017T100748), in part by Natural Science Basis Research Plan in Shaanxi Province of China (2016JQ5015)and in part by the project of State Key Laboratory of Electrical Insulation and Power Equipment in Xi’an Jiaotong University (EIPE17205, EIPE16301).
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Fund Information
supported in part by National Key Research and Development Program of China(2016YFB0901900); in part by the Science and Technology Project of SGCC-Research on Grid Dispatching and Transaction Mode for Global Energy Interconnection; in part by China Postdoctoral Science Foundation(2017T100748); in part by Natural Science Basis Research Plan in Shaanxi Province of China(2016JQ5015); in part by the project of State Key Laboratory of Electrical Insulation and Power Equipment in Xi’an Jiaotong University(EIPE17205,EIPE16301);
supported in part by National Key Research and Development Program of China(2016YFB0901900); in part by the Science and Technology Project of SGCC-Research on Grid Dispatching and Transaction Mode for Global Energy Interconnection; in part by China Postdoctoral Science Foundation(2017T100748); in part by Natural Science Basis Research Plan in Shaanxi Province of China(2016JQ5015); in part by the project of State Key Laboratory of Electrical Insulation and Power Equipment in Xi’an Jiaotong University(EIPE17205,EIPE16301);