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The increased injection of volatile renewable energy at local levels into the electricity grid is forcing the distribution network operators to seek participation in emerging service markets in order to obtain the flexibility required to balance their systems. However, the distribution companies lack experience in designing new market arrangements. We consider a market framework wherein a proactive distribution company is willing to purchase reserve capacity for overload management, using a two-part tariff. The problem is modelled as a three-stage stochastic market including Day-Ahead, Intra-Day and Real-Time, with uncertainty on both demand and generation. After assessing our formulation, we discuss the impact of risk-aversion at each stage with an objective function based on CVaR. Finally, different Intra-Day clearing horizons and delivery settings are evaluated. The results show that risk-aversion close to Real-Time becomes the main driver for decision makers and that early hedging strategies lead to sub-optimal solutions.

Increasing variable renewable power generation (e.g., wind) is expected to reduce wholesale electricity prices by virtue of its low marginal production cost. This merit-order effect of renewables displacing incumbent conventional (e.g., gas) generation forms the theoretical underpinning for investment decisions and policy in the power industry. This paper uses a game-theoretic market model to investigate how intermittently available wind generation affects electricity prices in the presence of forward markets, which are widely used by power companies to hedge against revenue variability ahead of near-real-time spot trading. We find that in addition to the established merit-order effect, renewable generation affects power prices through forward-market hedging. This forward effect reinforces the merit-order effect in reducing prices for moderate amounts of wind generation capacity but mitigates or even reverses it for higher capacities. For moderate wind capacity, uncertainty over its output increases hedging, and these higher forward sales lead to lower prices. For higher capacities, however, wind variability conversely causes power producers to behave less aggressively in forward trading for fear of unfavorable spot-market positions. The lower sales counteract the merit-order effect, and prices may then paradoxically increase with wind capacity despite its lower production cost. We confirm the potential for such reversals in a numerical study, suggesting new empirical questions while providing potential explanations for previously contradictory observed effects of market fundamentals. We conclude that considering the conventional merit-order effect alone is insufficient for evaluating the price impacts of variable renewable generation in the presence of forward markets. This paper was accepted by Vishal Gaur, operations management.

This paper contributes to the general consideration of whether a policy of incentivising improved forecasts for renewable energy outputs, and making them more available in the daily electricity market, would be beneficial. Using data from the German electricity market, we investigate the effect of wind and solar energy forecasts errors on imbalance volumes and intraday spot electricity prices. We use ordinary least square regression, quantile regression and autoregressive moving averages to identify these relationships using variables that have a quarter-hourly data granularity. The results show a positive relationship between wind forecast errors and imbalance volumes. We find that wind forecast errors impact spot prices more than solar forecasting errors. Policy incentives to improve the accuracy and availability of renewable energy forecasts should therefore be encouraged.

The rise of distributed energy resources (DERs) can enhance the efficiency of system operations by providing flexibility services to the different agents involved, but they also pose a major resource allocation problem. This study considers three different agents procuring DER services: distribution system operators (DSOs) for local congestion management, transmission system operators (TSOs) for system-wide reserve deployment, and retailers for hedging against network usage tariffs based upon peak-load pricing. A variety of market mechanisms are identified to co-ordinate these needs, and three schemes are developed in detail. These are separate markets for each agent, co-ordinated Shapley value allocations for TSO and DSO, and a co-ordinated mechanism including retailers. These designs are evaluated on a realistic distribution network in Britain for two operational days. The results show a more efficient dispatch from the TSO–DSO co-ordinated procurement over independent sequential procurements. However, the inclusion of retailers in the joint dispatch is surprisingly less attractive due to the lack of improvement in social welfare and the undesirable impacts on the DSO.

The transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support., OFGEM and the Low Carbon Network Fund

This thesis aims to make two types of academic contributions. It includes both methodological insights about the application of quantitative methods to the study of network industries and theoretical results concerning the economics of energy markets. The theoretical literature on interconnectors has established their potential to mitigate local market power, but the relationship between capacity utilisation and locational market splitting has not been studied empirically. Thus, in the first essay of the thesis I apply Vector Autorregressive (VAR) modelling techniques to data from the Bacton (UK)-Zeebrugge (Belgium) natural gas pipeline. The analysis identifies a threshold of capacity utilisation after which the UK and Continental markets split. The relationship between local price differences and capacity use is increasing and convex. A difference between the UK and Continental markets is that while there are extensive crossholdings in the Continent, UK firms remain in general independent from each other. This raises the issue of how crossholdings affect the firms' ability to coordinate in higher prices. Hence, the second essay presents a set of simulations in which computational agents try to optimise their profit using parameters adapted from the Roth and Erev (1995) reinforcement algorithm. The auction setting is a double-sided stylisation of the European energy markets. The results indicate that market transparency leads to higher prices, that the functional form of the crossholdings to prices relationship is not linear but concave and that more downstream competition reduces the influence of information on wholesale prices. The model in the third essay is complementary to the crossholdings research and incorporates key aspects of the interlinked operations of gas and electricity wholesale markets in the short-run. These sequential multiple-unit auctions present many non-Pareto ranked equilibria and we propose another Roth and Erev (1995) simulation as an alternative. The simulations unveil a new market power mechanism that explains why vertical market power can be observed in the energy industry.

The energy field has been dominated in recent years by two different themes: on the one hand, the integrated approach to energy planning, and, on the other hand, the ownership structures for industries' management. This thesis investigates a broad range of problems arising in relation to these themes, including demand-side management, technology diffusion and supply-side management. It also reviews the corresponding approaches to assist the decision making process in connection with these problems. It is shown here that there is a methodological vacuum with respect to the support tools for energy analysis due to emerging policy challenges in the energy field, and methodological solutions are proposed to this end. The contribution is thus primarily three fold: 1) a methodology to assist both policy analysis and strategic processes, 2) a systems platform to assess policy and strategy, and 3) evaluation of specific policy and strategic issues arising in the new liberalised environments being implemented in both the British and Colombian energy systems. In this case, methodological connections are appropriate as the Colombian Government has incorporated aspects of the British energy system set-up. This thesis contains seven chapters. Chapter 1, from an extensive literature review, establishes a dilemma in relation to the methodology required to support system analysis and planning. Chapter 2 presents a new methodological proposal to meet the requirements. Chapter 3 concept-tests the proposal and specifies an analysis-support platform as a generic aid to modelling. Chapter 4 develops a case study for the UK energy system, partially testing the proposed approach and the analysis platform especially constructed for this situation. Chapter 5 elaborates upon a case study for the Colombian energy sector, examining in detail both methodology and the analysis platform uniquely designed for this case. Chapter 6, with the support of a platform construct, studies and assesses energy policies for Colombia. Finally, Chapter 7 summarises and concludes the major findings of this thesis.