Measuring the impact of market coupling on the Italian electricity market using ELFO++

This paper evaluates the impact on the Italian electricity market of replacing the current explicit auction mechanism with market coupling. Maximizing the use of the cross-border interconnection capacity, market coupling increases the level of market integration and facilitates the access to low-cost generation by consumers located in high-cost generation countries. Thus, it is expected that a high-priced area such as Italy could greatly benefit from the introduction of this mechanism. In this paper, the welfare benefits are estimated under alternative market scenarios for 2012, employing the optimal dispatch model ELFO++. The results of the simulations suggest that the improvement in social surplus is likely to be significant, especially when market fundamentals are tight.Market coupling; market integration; Italian day-ahead electricity market.

Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market: A Proposed Merchant-Regulatory Mechanism

We propose a merchant-regulatory framework to promote investment in the European natural gas network infrastructure based on a price cap over two-part tariffs. As suggested by Vogelsang (2001) and Hogan et al. (2010), a profit maximizing network operator facing this regulatory constraint will intertemporally rebalance the variable and fixed part of its two-part tariff so as to expand the congested pipelines, and converge to the Ramsey-Boiteaux equilibrium. We confirm this with actual data from the European natural gas market by comparing the bi-level price-cap model with a base case, a no-regulation case, and a welfare benchmark case, and by performing sensitivity analyses. In all cases, the incentive model is the best decentralized regulatory alternative that efficiently develops the European pipeline system.regulation, transportation network, investment

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Renewable Electric Energy Integration: Quantifying the Value of Design of Markets for International Transmission Capacity

Integrating large quantities of supply-driven renewable electricity generation remains a political and operational challenge. One of the main obstacles in Europe to installing at least 200 GWs of power from variable renewable sources is how to deal with the insufficient network capacity and the congestion that will result from new flow patterns. We model the current methodology for controlling congestion at international borders and compare its results, under varying penetrations of wind power, with a model that simulates an integrated European network that utilises nodal/localised marginal pricing. The nodal pricing simulations illustrate that congestion - and price - patterns vary considerably between wind scenarios and within countries, and that a nodal price regime could make fuller use of existing EU network capacity, introducing substantial operational cost savings and reducing marginal power prices in the majority of European countries.Power market design, renewable power integration, congestion management, transmission economics

A market-based transmission planning for HVDC grid—case study of the North Sea

There is significant interest in building HVDC transmission to carry out transnational power exchange and deliver cheaper electricity from renewable energy sources which are located far from the load centers. This paper presents a market-based approach to solve a long-term TEP for meshed VSC-HVDC grids that connect regional markets. This is in general a nonlinear, non-convex large-scale optimization problem with high computational burden, partly due to the many combinations of wind and load that become possible. We developed a two-step iterative algorithm that first selects a subset of operating hours using a clustering technique, and then seeks to maximize the social welfare of all regions and minimize the investment capital of transmission infrastructure subject to technical and economic constraints. The outcome of the optimization is an optimal grid design with a topology and transmission capacities that results in congestion revenue paying off investment by the end the project's economic lifetime. Approximations are made to allow an analytical solution to the problem and demonstrate that an HVDC pricing mechanism can be consistent with an AC counterpart. The model is used to investigate development of the offshore grid in the North Sea. Simulation results are interpreted in economic terms and show the effectiveness of our proposed two-step approach

Regulating transmission in a spatial oligopoly: a numerical illustration for Belgium

This paper introduces strategic behavior of the electricity network operator in a congested network with imperfect competition for generation. It models a two stage Stackelberg game. First, the network operator sets transmission prices, then generators set output and sales. Several scenarios for the generation market structure and the behavior of the network operator are compared numerically. The calibration of the numerical model is based on data of the Belgian electricity market.Regulation, Transmission, Electricity, Cournot, Numerical model, Security constraints, MPEC, loadflow, Belgium

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence.Electricity, liberalisation, market power, regulation

On the interaction between Autonomous Mobility-on-Demand systems and the power network: models and coordination algorithms

We study the interaction between a fleet of electric, self-driving vehicles servicing on-demand transportation requests (referred to as Autonomous Mobility-on-Demand, or AMoD, system) and the electric power network. We propose a model that captures the coupling between the two systems stemming from the vehicles' charging requirements and captures time-varying customer demand and power generation costs, road congestion, battery depreciation, and power transmission and distribution constraints. We then leverage the model to jointly optimize the operation of both systems. We devise an algorithmic procedure to losslessly reduce the problem size by bundling customer requests, allowing it to be efficiently solved by off-the-shelf linear programming solvers. Next, we show that the socially optimal solution to the joint problem can be enforced as a general equilibrium, and we provide a dual decomposition algorithm that allows self-interested agents to compute the market clearing prices without sharing private information. We assess the performance of the mode by studying a hypothetical AMoD system in Dallas-Fort Worth and its impact on the Texas power network. Lack of coordination between the AMoD system and the power network can cause a 4.4% increase in the price of electricity in Dallas-Fort Worth; conversely, coordination between the AMoD system and the power network could reduce electricity expenditure compared to the case where no cars are present (despite the increased demand for electricity) and yield savings of up $147M/year. Finally, we provide a receding-horizon implementation and assess its performance with agent-based simulations. Collectively, the results of this paper provide a first-of-a-kind characterization of the interaction between electric-powered AMoD systems and the power network, and shed additional light on the economic and societal value of AMoD.Comment: Extended version of the paper presented at Robotics: Science and Systems XIV, in prep. for journal submission. In V3, we add a proof that the socially-optimal solution can be enforced as a general equilibrium, a privacy-preserving distributed optimization algorithm, a description of the receding-horizon implementation and additional numerical results, and proofs of all theorem