Optimal energy pricing for integrated natural gas and electric power network with considerations for techno-economic constraints
Introduction
Utilization of energy planning based on bottom-up approach has given rise to opportunities for substitution of energy carriers [1]. However, for effective planning, the interdependency of energy carriers requires examination of price relation between them with considerations for techno-economic aspects [2]. Motivated by guarantee of rewards for suppliers, optimal pricing for energy carriers can serve as an effective mechanism for assisting consumers to make the necessary adjustments in their consumption. As such, social welfare of both suppliers and consumers are met while preserving energy resources. In the long run, it is also expected that energy generation, transmission, and distribution development and investment, as well as the quality of energy services can be improved, when optimal energy pricing is implemented. A careful examination of these issues reveals that energy pricing is a techno-economic problem, where parameters such as fuel price volatility, congestion, contingency, distance, and power generation efficiency affect the pricing scheme for different locations in energy networks, as it has recently been posed as a part of deregulated energy market [3].
Based on the realization of price relation between energy carriers, in several South America countries, where fossil fuels are regarded as the necessary feed for power generation, natural gas (NG) market joined the electricity market forming the first experiment of “integrated energy markets” [4]. Numerous studies have been conducted to examine the techno-economic aspects of NG network (GN) and electric power network (PN) in an integrated way, namely, the work by An et al., in 2003, where it is demonstrated that higher social welfare from integrated natural gas and power network (IGPN) is achievable, as compared with that from GN and PN on individual basis [2].
The key result from IGPN analyses is the pricing of the respective energy carriers as a function of production cost, generation and transmission capital cost, operating and maintenance cost, power quality supply cost, loss and congestion costs, producers rate of interest, and aggregated consumers demand pattern [3].
Next, to provide the needed background for achieving the objective of this study, the literature review on development of IGPN modeling and outcomes from previous studies are discussed.
Section snippets
Literature review
An et al. examined an integrated NG and electricity optimal power flow (GEOF) in 2003 based on primal dual interior point algorithm (IPA) for optimization and maximizing social welfare and, in a case study, two scenarios for the wellhead NG price are introduced to determine the sensitivity of generated power to such pricing approach [2]. While techno-economic issues are not addressed in that study, the findings show that the social welfare decreases if the optimal NG flow and optimal power flow
IGPN modeling and problem formulation
In the IGPN analyzed in this study, as shown in Fig. 1, the PN has five buses with two power plants where power plant G1 utilizes coal (CFPP) with fixed coal price and power plant G2 operates with NG (GFPP) fed from g15 of the GN [2]. Table 1(a), Table 1(b), Table 1(c), Table 1(d), Table 1(e), Table 1(f), Table 1(g)(a)-(g) show IGPN parameters specifications including the allowed range for production of NG resources and NG loads, GN nodes pressures, GL physical characteristics, gas turbine
Optimality conditions
The energy pricing optimization formulation of IGPN described by Eq. (25) can be written as a general nonlinear programming problem,subject to:where is a general notation for objective function and are sets of equality and inequality constraints, respectively. The lower and upper limits of inequality constraints are and lower and upper limits for variables are , respectively. The implementation of IPA encompasses four steps,
Scenarios
For the purposes of studying the effects of techno-economic constraints and examination of interdependencies of optimal GLMP and ELMP, several scenarios are introduced. Scenario NORM is defined to reveal the results of optimization in IGPN under normal operation and, to serve as the basis for comparison of the obtained results with those of other scenarios. The motivation for definition of RPF, RGF, and RGPF is to simulate the conditions in which a typical GL or PL are not able to carry more NG
Results and discussion
The simulation results for optimal energy pricing of the IGPN analyzed in this study based on the scenarios described above are discussed in this section. It is emphasized that, in this study, the interdependency of energy prices is observed and GLMP (at GN nodes) and ELMP (at PN buses) are determined simultaneously, based on TEC minimization for the IGPN. As shown in Table 1(a), Table 1(f)(a) and 1(f), with the exception of NG load for GFPP, other NG and electrical loads are constant. To
Conclusions and recommendations
In this study, the optimal locational marginal prices for an IGPN are examined based on IPA for optimization, where various techno-economics constraints are accounted for. The effects of techno-economic constraints considered are analyzed based on several scenarios and, it is found that the results of optimal pricing in this study are highly dependent on IGPN topology examined. Hence, the following conclusions can be drawn.
- (a)
The variation of GLMPs is not affected by PN conditions dramatically,
Acknowledgements
The assistance received from A. Sadri at Energy Systems Laboratory during the preparation of the manuscript is appreciated.
Nomenclature
Acronyms
- CFPP
- coal-fired power plant
- CHP
- combined heat and power
- DIS
- influence of distance between GFPP and natural gas network (scenario)
- ED
- Economic Dispatch
- EIA
- Energy Information Administration
- ELMP
- electricity locational marginal price
- GEOF
- natural gas and electricity optimal power flow
- GFPP
- gas-fired power plant
- GL
- natural gas pipeline
- GLMP
- natural gas locational marginal price
- GN
- natural gas network
- GTC
- gas turbine compressor
- IGPN
- integrated power and natural gas network
- IMP
- GFPP improvement efficiency (scenario)
- IPA
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