Carlos Vergara , Esteban Gil , Ignacio Calle , Sergio DÃaz and Jorge Velásquez. Abstract. As penetration of variable renewable generation increases, many ...
Technical constraints in fossil fuel generators: impacts on long-term investments signals 1
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1
1
Carlos Vergara , Esteban Gil , Ignacio Calle , Sergio Díaz and Jorge Velásquez 1
1
Department of Electrical Engineering , Technical University Santa María, Valparaíso, Chile 2
Advanced Center for Electrical and Electronics Engineering (AC3E), Valparaiso, Chile
Case 1 Case 1
Abstract As penetration of variable renewable generation increases, many conventional thermal power plants need to operate long hours at their minimum stable levels (MSL) due to operational constraints. In these conditions, they may be generating at times when the price of the system is below their marginal costs, incurring in economic losses and hurting their profitability. This paper discusses how operational inflexibility of some fossil fuel generators will impact long-term generation capacity expansion planning decisions. Many thermal power plants may need to operate long hours close to their MSL to avoid switching off when plenty of solar or wind energy is being injected into the system. Operation under these conditions will usually cause them negative revenues, as their marginal costs may be below the marginal price of the system. This may happen for both bid-based and cost-based markets. Under these conditions, inflexible thermal generators are facing increasingly longer periods with negative revenues, hurting their profitability. However, these issues are ussually not reflected in long-term capacity expansion models, wich may provide the wrong signals for investors as operational flexibility is not accounted for in current mathematical optimization models. Technology Technology
Investment without considering MSL [MW]
Methodology
2500
Case 1 Purpose
Test system
Find differences in the Diesel amount of installed c a p a c i t y b y Total technology, with and without considering MSL constraints.
Ÿ Ÿ Ÿ
Demand approach
Constraints
Single node 3 types of generation C o n t i n u o u s investment decision variables
2500
Case 2
CC-LNG
Case 3
1768
1376
Identify differences for 0 the investment timing, considering an 4268 economically adapted system with and without considering MSL constraints. Ÿ Ÿ Ÿ
Single node 3 types of generation Discrete investment decision variables
MSL
2500
CC-LNG
1768
1376
Diesel
0
392
Total
4268
4268
Case 2 Investment per technology without/with considering MSL [number of units] Technology\Year
5
6
7
8
CC-LNG
1/0
0/1
1/1
1/0
Diesel
0/1
Coal Modified SING (Chilean Northern Interconnected System).
Ÿ
Ÿ
Pyomo
2500
4268
Ÿ
Simulation tool Pyomo
Coal
392
6 load blocks per year 1 load per year block for Comparison between f o r o n l y o n e - y e a r 15-year horizon. Full chronological horizon. versus LDC approach for 15-year horizon. MSL
Investment considering MSL [MW]
Investment considering MSL [MW]
In order to analyze the investments signals with and without modeling MSL of fossilfuel generators, three simulations cases are considered: Coal
Investment without considering MSL [MW]
Technology\Year
1
2
2/2
9
3
4
1/1
10
11
12
13
14
15
1/0
1/1
1/1
1/1
1/1
1/1
Coal CC-LNG Diesel
MSL Min up time Min down time
0/1
Case 3
PLEXOS
Problem Formulation
Investments considering MSL and operation times constraints.
Investments without considering MSL and operation times constraints.
Conclusions Ÿ Explicitly modeling flexibility constraints in GCEP problems have an
Ÿ Including other inter-temporal constraints of thermal units may
impact on the technologies chosen and the timing of investment decisions. Ÿ When MSL constraints are considered, flexible generation may be preferred to inflexible generation despite having higher operational cost.
motivate to move forward some investment decisions. Ÿ If MSL constraints are not accounted for in CEP models, inflexible generators may end up dispatched fewer hours than expected.
