Search

Transitioning from fossil fuel dominated power systems to high penetrations of intermittent renewable generation is affecting classical electricity market designs. Here, a method is proposed to model and assess the absence of co-optimization of energy and reserve that prevails in the European system. Co-optimization is formulated through an optimization problem (COM), and its absence as an equilibrium problem (EQM) built on Karush-Kuhn-Tucker conditions of agents’ optimization and market clearing equations. EQM cannot be reformulated as a single optimization problem. Market distortions are identified by comparing the complementarity conditions of both models. These are then discussed on system with Feed in Premium to wind generation. Parameters in the models allow to represent different market configurations regarding: available wind generation, Feed in Premium to wind, generators’ risk aversion, and required reserve from wind generation. [ABSTRACT FROM AUTHOR]

Microgrid (MG) represents one of the major drives of adopting Internet of Things for smart cities, as it effectively integrates various distributed energy resources. Indeed, MGs can be connected with each other and presented as a system of multimicrogrid (MMG). This paper proposes the optimal operation of MMGs by a cooperative energy and reserve scheduling model, in which energy and reserve can be cooperatively utilized among MMGs. In addition, values of Shapely are introduced to allocate economic benefits of the cooperative operation. Finally, a case study based on a system of MMGs is conducted, and simulation results verify the effectiveness of the proposed cooperative scheduling model. [ABSTRACT FROM AUTHOR]

This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability.

The cross-border trading among electricity markets in an interconnected multi-area system (e.g., in central Europe) and the integration of renewable resources (e.g., wind energy) have remarkably increased in recent years. To efficiently operate such system, a proper coordination among different areas is required. Within this context, a decentralized algorithm for market clearing is proposed in this paper to dispatch simultaneously energy and reserve under wind generation uncertainty and equipment failures. The proposed technique does not require a central operator but just a moderate interchange of information among neighboring areas. Additionally, the benefit of cross-border trading is studied. [ABSTRACT FROM PUBLISHER]

• Planning the capacity expansion of the European power system towards 2050. • Using stochastic optimization to consider the long- and short-term uncertainties. • Operating the energy and reserve markets of the European power system in 2050. • Huge production of intermittent renewable power is possible with storage capacity. • Sixteen countries will end up with a generating system at least 70% renewable. In this paper we study the European power system for 2050 from both the expansion and the operation perspectives. First, the generating and storage capacity to be built is decided by solving a multi-stage investment model taking into account the uncertainty related to the investment costs and the demand growth. Stochastic programming is used to represent this decision-making problem under uncertainty. Second, the daily operation of the resulting European power system is analyzed. A two-stage stochastic-programming problem is proposed to model the day-ahead energy and reserve markets in the first stage, and the real-time operation in the second stage. At this level, the uncertainty of the hourly available wind and solar power and the demand level is considered. The numerical results indicate that an European power system mainly based on solar and onshore wind power is possible at a reasonable cost if storage units are also installed. The total new generating capacity to be built up to 2050 will be around 881 GW, which leads to an investment cost of at least 1622 billion euros. The possibility of wind, solar and storage units to provide a certain reserve capacity allows to reduce the participation of thermal units. Therefore, a 77% reduction in the CO 2 emissions respect to 1990 may be achieved in 2050. Finally, unserved demand is found in few countries only in 75 h of the year, while the average daily energy prices are stable and comparatively low among the countries. [ABSTRACT FROM AUTHOR]

This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability. [ABSTRACT FROM AUTHOR]