Abstract
We consider strategic gas/power producers and strategic gas/power consumers operating in both gas and power markets. We build a flexible multi-period complementarity model to characterize day-ahead equilibria in those markets. This model is an equilibrium program with equilibrium constraints that characterizes the market behavior of all market agents. Using a realistic case study, we analyze equilibria under perfect and oligopolistic competition. We also analyze equilibria under different levels of information disclosure regarding market outcomes. We study as well equilibria under different ownership schemes: no hybrid agent, some hybrid agents, and only hybrid agents. Finally, we derive policy recommendations for the regulators of both the gas and the power markets.
Highlights
Electric power systems and natural-gas systems are generally operated independently, with limited or no coordination [1]
Since Mathematical Program with Equilibrium Constraints (MPEC) (9)–(12) might be complex to solve/transform and considering that the gas problem is formulated as a second order conic problem (SOCP) [21] and that the power problem is formulated as a linear programming problem, each of these problems can be replaced by its primal constraints, its dual constraints, and its strong duality equality
We observed that the equilibrium model that maximized Total Producers’ Profit (TPP) yielded a lower SW but a higher TPP than the corresponding SW and TPP
Summary
Electric power systems and natural-gas systems are generally operated independently, with limited or no coordination [1]. Byeon and Van Hentenryck [4] introduce a unit commitment problem with gas network awareness, where bid-validity constraints are imposed on gas-fired units He et al [5] propose an integrated gas and power system operation model that considers demand response and uncertainty via distributionally robust optimization. We propose in this paper an equilibrium model that allows studying the interactions of both gas/power producers and gas/power consumers (referred generically to as agents) through both the gas and the power markets. This model expands the one reported in [17] as it considers a multi-period framework and carries out a comprehensive analysis. We provide detailed descriptions of the models considered and metrics used
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