The paper addresses the problem of supporting research of the Vietnam energy sector vulnerability. The vulnerability study is understood as search for system weak points. A mathematical model has been developed to describe the energy sector of Vietnam. The model takes into account the characteristics and constraints of all objects of the energy sector: suppliers, consumers and the transport system. To study the vulnerability of the energy sector and make decisions, we have created a workbench that allows simulating increased loads and calculating the consequences. Specification-based database application development technology was applied to create the workbench. This technology allows you to quickly develop applications that provide interaction with databases and digital maps, as well as support interaction with external software modules. The main advantage of the proposed workbench is its flexibility and applicability at all stages of the study of the Vietnam energy sector vulnerability starting from gathering the energy operation and development information and ending with evaluation of satisfying demand in energy.
The resilience of an energy system can be understood as the system ability to prevent
damage before disturbance events, mitigate losses during the events, and improve the
recovery capability after the events [
The main stages of the interdependent energy systems resilience research scheme
are presented in [
The vulnerability analysis process consists of the following general stages: Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 1. gathering an energy sector operation and development information 2. calculation on an energy sector model 3. solution data processing 4. solution data presentation 5. evaluation of satisfying demands
A workbench presented in this paper supports the vulnerability analysis of Vietnam energy sector and automates the stages from 2 to 5. 2
Decision support systems have a critical role in assessing the natural disasters risk of
energy systems networks and in enabling their managers to test the effectiveness of
alternative mitigation strategies and investments on resilience [
A GIS technology play a major role in the construction of such decision support
systems [
The workbench represents ways of energy sector development as a directed graph (see Fig. 1). The first moment is always equal 0 and presents the current year. Each node of the graph represents the energy sector state at specific moment (year) in the future. Each arc defines a transition from state at one moment in time (year) to another state at next moment in time (year).
Each node of the energy sector development graph is associated with the following information about the energy sector: • demands in energy; • energy transmission capacity and cost; • energy production capacity and cost; • energy transformation capacity and cost.
Thus energy sector development scenario is described as sequence of nodes at different time moments:
Node 0 — the energy sector model data for initial time moment Node 1 — the energy sector model data for second time moment Node 2 — the energy sector model data for third time moment
Node 3 and further — energy sector model data for next time moment 3.1
The Vietnam energy sector model is based on the initial information of one of the national energy sector perspective development plans. Analysis of such options by means of the energy sector model can address the following specific strategic challenges of Vietnam energy sector development: • the deployment of new energy sources of different kinds around the country, including nuclear power plants; • the deployment of energy resources import entries on the area of the country; • the order of the creation of new facilities of coal mining, natural gas extraction, crude oil extraction and refining taking into account the capabilities of existing and new energy resources transmission lines, etc.
A general energy sector model consists from the following equations and inequalities: (C,X) + ( ,g) →
AX− = 0 0 ≤ ≤ 0 ≤ ≤ (1) (2) (3) (4)
The first part of the goal function represents total costs of the FEC operation. The is the cost vector of the energy resources production and transmission facilities.
The second part of the goal function characterizes financial losses due to energy resource shortages. The vector is equal to the difference ( − ). The is cost vector of energy resource shortages. The estimation of real costs of damage from a shortage is difficult due to variety of shortage after-effects, which are not always possible to identify and quantify. 3.2
There is a one digital map per each energy recourse distribution net. Each digital map should consists of 3 layers: 1. Consumers as polygon type layer; 2. Producers as point type layer; 3. Transmission links as line type layer.
To show state by color coloring rules for each layer type were created. Coloring rules for consumers are shown in Table 1. Colors of energy resource producer according to 1 are shown in 4. Colors of energy resource transmission link according to 2 are shown in 5. Colors of energy resource consumer according to Table 3 are shown in table 6.
4 4.1
The energy sector model describes the following major energy systems of Vietnam: • Gas supply system consists of natural gas fields which are combined into gasproducing areas and possible entries of imported liquefied natural gas. Natural gas transport within the country is represented by network of existing and new gas pipelines. • Coal supply system. Coal mines can be aggregated by locality. The qualitative structure of coals can be taken into account by separation of particular kinds. Transport of coal between regions matches directions of the main cargo transfer paths. • The crude oil refinery products supply system can be represented by the production and distribution of light oil and fuel oil. Transportation of petroleum products is represented by set roads, marine links and railways between producers and consumers. • Power system. Power plants are divided into several types: thermal, hydro, nuclear power plants and renewable energy sources. Thermal power plants are classified by type of main fuel: natural gas, coal and fuel oil. Renewable energy source are divided into the solar cells, wind farms and thermal power plants using biomass.
Except for the production and transportation blocks in the energy sector model there is a block of consumption, which is represented by the main consumers of the energy sector, ranked by category of importance. 4.2
The main symbols used in this paper are described below for quick reference. Indices – amount of regions p, r ∈ {1, } – order number of region ∈ {a,b,g,z,e,o,u,h,d,k,w} – energy resource, where – anthracite; – brown coal; – natural gas; – LPG; – electricity; – crude oil; – gasoline; ℎ – FO; – DO; – kerosene;
– aviation gasoline; Input parameters ∈a,b,g,z,o,u,h,d,k,w ¯ – up value of capacity to produce or extract energy resource in region , ¯rp – up value of capacity to transmit energy resource from region to region , ∈ {a,b,g,e,z,o,u,h,d,k,w} ¯rp – up value of capacity to export energy resource from region to region , – up value of energy resource demand in region , ∈ {e,z,o,u,k,w} – up value of total capacity of TPS burning fuel in region , ∈ {a,b,g,h,d} – value of burning fuel to generate one unit of electricity on TPS in region , ¯ oth – up value of others sources total capacity in region ¯ NPP – up value of total nuclear power plants (NPP) capacity in region ¯ HPS – up value of total hydro power stations (HPS) capacity in region =
¯ – crude oil refinery coefficient for energy resource production in region ∈ {a,b,g,e,z,o,u,h,d,k,w}
¯ TPS,l ∈ {a,b,g,h,d} rp rp – – , ∈ {h,d,k,w,z} Output parameters ∈ {a,b,g,z,e,o,u,h,d,k,w} ∈ {a,b,g,z,e,o,u,h,d,k,w} – energy resource production in region , ∈ {a,b,g,z,o,u,h,d,k,w} transport of energy resource from region export of energy resource from region to to region , region , NPP – power generation by NPP in region HPS – power generation by HPS in region – energy resource consumption in region , ∈ {e,z,o,u,k,w} TPS,l – power generation by TPS burning fuel in region , ∈ {a,b,g,h,d}
oth – power generation by other sources in region Cost rp rp – cost of energy resource produced in region , ∈ {a,b,g,z,o,u,h,d,k,w} TPS,l – cost of power generated by TPS burning fuel in region , ∈ {a,b,g,h,d} HPS – cost of power generated by HPS in region NPP – cost of power generated by NPP in region oth – cost of power generated by other sources in region from region to region , ∈ {a,b,g,z,e,o,u,h,d,k,w} – cost of one unit of energy resource transmission (transportation or import) – losses due to one unit of exported energy resource non-delivery from region to region , ∈ {a,b,g,z,e,o,u,h,d,k,w} region , ∈ {a,b,g,z,e,o,u,h,d,k,w} – losses due to one unit of energy resource non-delivery for consumption in Q
+ ∑ ≠ pr − ∑ ≠ rp − ∑
≠ rp − S Anthracite balance in region Brown coal balance in region
Q + ∑
≠ pr − ∑
≠ rp − ∑
≠ rp − S Q + ∑
≠ pr − ∑
≠ rp − ∑
≠ rp − S Crude oil balance in region
TPS,g TPS,a TPS,b -D -D -D g a b ≥ 0 ≥ 0 ≥ 0 4.3
Natural gas balance in region Q + ∑
≠ pr − ∑
≠ rp − ∑
≠ rp − ≥ 0
+ + ∑
≠ pr − ∑
≠ rp − ∑ ≠ rp -D ≥ 0 Aviation gasoline balance in region Q + + ∑
≠ pr − ∑
≠ rp − ∑
≠ rp -D ≥ 0 Electricity balance in region ∑
Up values of energy resource production in region
0 ≤ ≤ ¯ , ∈ {a,b,g,z,o,u,h,d,k,w} Up values of power generation by TPS burning fuel in region , ∈ {a,b,g,h,d} Up values of NPP power generation in region Up values of HPS power generation in region Up values of power generation by other sources in region 0 ≤ TPS,l ≤ ¯ TPS,l 0 ≤ NPP ≤ ¯ NPP 0 ≤ HPS ≤ ¯ HPS 0 ≤ oth ≤ ¯ oth Up values of energy resource transport between region and 0 ≤ rp ≤ ¯ rp, ∈ {a,b,g,e,z,o,u,h,d,k,w}
Up values of energy resource export between region and
0 ≤ rp ≤ ¯ rp, ∈ {a,b,g,e,z,o,u,h,d,k,w} Up values of consumption of energy resource in region
0 ≤ ≤ , ∈ {e,z,u,k,w} 4.4
EXPORT + LOSS ]
GEN = ∑l={a,b,g,h,d}
TPS,l TPS,l +c NPP NPP+c HPS HPS+c oth oth EXPORT = ∑ ≠ ∑l={a,b,g,e,z,o,u,h,d,k,w} rp
rp LOSS = ∑l={a,b,g,e,z,o,u,h,d,k,w}
−
To find minimum of goal function (24) is to find costs minimum. Equation (25) is energy resources non-delivery inside country. total power generation of region . Equation (26) is total region losses due to energy resources non-delivery outside country. Equation (27) is total region losses due to ∑ [∑l={a,b,g,z,o,u,h,d,k,w} + GEN + ∑ ≠ ∑l={a,b,g,e,z,o,u,h,d,k,w} rp rp + 5
For vulnerability study of energy sector, an expert needs to be able to interact with source data of the energy sector model, prepare data for calculations, configure and execute calculations, and view results. Energy sector model objects are represented as relational database entities. Therefore, database interaction is one of base functions of the information system for studying the vulnerability of the energy sector. (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27)
Information systems that provide the implementation of СRUD (create, read,
update, delete), search and some other operations (for example, reports generation) are
called database applications. Database application development is a routine and
timeconsuming process because you have to perform many repetitive steps. Indeed, the
code parts, which implement the typical operations for different tables usually have
no substantial differences, besides from the names of the used tables and fields. There
are approaches to partially automate the development of database applications. For
example, using the Hibernate / NHibernate [
Also, a model-oriented approach is used for automate the development of database
applications. For example, "Model-Based User Interface Development" [
We used an approach based on the use of specifications of database applications
(SDA) [
The Workbench for vulnerability analysis of energy sector (see Fig. 2) created with the help of GeoARM provides interaction with the entities of the ES database in the modes of tables and individual records, and also allows you to build user queries and display information on digital maps. Researcher can generate map objects if there are fields in the database with the coordinates of the objects. You can also display on the map the result of a user query to the database. In this case, you can set the color of objects on the map depending on the values of a specific field of the query result. We can run compute modules that return results to the database. Further, based on the results obtained, we can create digital map objects and carry out analysis. In addition, you can display the result of a custom query to the database on the map. At the same time, you can set the color of objects on the map depending on the values of a specific characteristic of objects in the energy sector.
A special tool has been developed to provide calculation on the model (5)-(27). The calculation module reads the Vietnam energy sector operation and development information from database and arranges that data into a development scenario (Fig 1). Then the module transforms the particular data associated with each node of directed graph shown in Fig. 1 into the linear programming problem (5)-(27) and solves the constructed problems sequentially. Thus the module can help to analyze time series of different energy sector parameters. 7
In the paper, we considered the problems concerned supporting the research of the Vietnam energy sector vulnerability. Conducting vulnerability studies requires a lot of efforts to prepare data, process data, perform calculations and analyze the results. The vulnerability analysis support requires user-friendly software that allows one to process data, run calculation modules, analyze and display the results.
We have developed a workbench to support the vulnerability analysis of interdependent national energy systems. The workbench is based on structural specifications that allow standardized solutions to the wide range of problems. The developed workbench allows us to solve the following tasks: • Interact with the database through a convenient user interface, • Execute external calculation modules, • Conduct data analysis: build queries to the database, build thematic maps in the GIS.
An example of the workbench to support finding the Vietnam energy sector vulnerability analysis was considered. It is shown that the described tools provides the flexible prototyping and fast implementation of applications. And in comparison with other approaches, the main advantage of proposed workbench is that it is applicable for all stages of the vulnerability analysis starting from gathering the energy operation and development information and ending with evaluation of satisfying demand in energy. 8
The research was supported by the Program of the Fundamental Research of the Siberian Branch of the Russian Academy of Sciences, project no. IV.38.1.2 (reg. no. АААА-А17-117032210079-1). The development of the calculation module was supported by the Russian Foundation of Basic Research and Government of Irkutsk Region, project no. 20‑47‑380002 (reg. no. АААА-А20-120021090008-7). Results are achieved using the Centre of collective usage «Integrated information network of Irkutsk scientific educational complex».