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This paper proposes a new mechanism for forward selling renewable electricity generation. In this transactive framework, a wind or solar farm may directly sell to consumers a claim on their future power output in the form of nonfungible blockchain tokens. Using the flexibility of smart contract code, which executes irrevocably on a blockchain, the realised generation levels will offset the token holders' electricity consumption in near real-time. To elucidate the flexibility offered by such smart contracts, two ways of structuring these power delivery instruments are considered: firstly, an exotic tranched system, where more senior tokens holders enjoy priority claims on power, as compared against a simpler pro-rata scheme, where the realised output of a generator is equally apportioned between token holders. A notional market simulation is provided to explore whether, for instance, consumers could exploit the flatter power delivery profiles of more senior tranches to better schedule their responsive demands.

Market power is a dominant feature of many modern electricity markets with an oligopolistic structure, resulting in increased consumer cost. This work investigates how consumers, through demand response (DR), can mitigate against market power. Within DR, our analysis particularly focusses on the impacts of load shifting and self-generation. A stochastic mixed complementarity problem is presented to model an electricity market characterised by oligopoly with a competitive fringe. It incorporates both energy and capacity markets, multiple generating firms and different consumer types. The model is applied to a case study based on data for the Irish power system in 2025. The results demonstrate how DR can help consumers mitigate against the negative effects of market power and that load shifting and self-generation are competing technologies, whose effectivity against market power is similar for most consumers. We also find that DR does not necessarily reduce emissions in the presence of market power.

Power systems based on renewable energy sources (RES) are characterised by increasingly distributed, volatile and uncertain supply leading to growing requirements for flexibility. In this paper, we explore the role of demand response (DR) as a source of flexibility that is considered to become increasingly important in future. The majority of research in this context has focussed on the operation of power systems in energy only markets, mostly using deterministic optimisation models. In contrast, we explore the impact of DR on generator investments and profits from different markets, on costs for different consumers from different markets, and on CO2 emissions under consideration of the uncertainties associated with the RES generation. We also analyse the effect of the presence of a feed-in premium (FIP) for RES generation on these impacts. We therefore develop a novel stochastic mixed complementarity model in this paper that considers both operational and investment decisions, that considers interactions between an energy market, a capacity market and a feed-in premium and that takes into account the stochasticity of electricity generation by RES. We use a Benders decomposition algorithm to reduce the computational expenses of the model and apply the model to a case study based on the future Irish power system. We find that DR particularly increases renewable generator profits. While DR may reduce consumer costs from the energy market, these savings may be (over)compensated by increasing costs from the capacity market and the feed-in premium. This result highlights the importance of considering such interactions between different markets.

Demand Response (DR) is capable of reducing the need for generation capacity investments in order to ensure system security. We utilise this fact to devise a novel methodology for estimating a load-shifting DR resource's capacity contribution and therefore determining DR's potential for participation in capacity markets. DR primarily affects the equilibrium outcome through the energy market, however DR also reduces prices and consumer costs through its capacity market contribution when there is a high level of variable renewable generation and initial undercapacity. As wind levels increase, so do capacity prices as generators seek higher capacity prices to offset depressed energy prices. However, we find that DR's participation in the capacity market can combat these increased capacity prices. These results suggest that DR participation in capacity markets can mitigate some of the market challenges of renewable integration.

To guarantee European countries with greater access to competitive energy sources, the European Union has identified new infrastructures for the achievement of a diversified, secure and affordable European single energy market. This paper aims to evaluate the impact on consumers' energy bill of new LNG and gas storage facilities. We focus on the integrated UK-Ireland gas system, which provides an interesting framework to assess socioeconomic benefits of new energy routes. We utilise a stochastic mixed complementarity problem model, which also incorporates stochastic gas supply cost and demand scenarios. Therefore, we assess the expected benefits for consumers of a diversified gas supply, and their sensitivity to changing market conditions. Our results imply the complementary of LNG and gas storage investments to manage shortterm peak loads and long-term seasonal loads and prices in gas markets. Nonetheless, economic benefits for consumers are dependent on market conditions. Overall, our results provide some suggestions on investments in new gas facilities, which are of interest to policy-makers and market participants.

Energy systems based on renewables have an increasing demand for flexibility. In this paper, we consider the potential of power-to-gas to provide flexibility and enhance the system integration of renewables. Existing research on power-to-gas typically analyses the system effects of a predetermined power-to-gas unit without endogenising the investment decision. Moreover, insights related to the market and portfolio effects of power-to-gas are rare. To this end we present a stochastic mixed complementarity problem, which models the optimisation problems of different market players individually. The players we consider include power generating firms with different generation portfolios and different consumer groups. Firms earn revenues from an energy market, a quantity-based capacity market and a feed-in premium for renewable generation. They maximise their profits by optimising the operation of existing assets and making investments in new generation assets and in power-to-gas. We find that firms with renewable generation benefit from investing in power-to-gas. While the technology itself is loss-making, power-to-gas particularly increases demand and hence prices in low-load hours. Therefore, renewable generation becomes more profitable, which justifies the investment. However, the price increase results in higher costs to consumers so the overall transfer from consumers to wind generators increases in the presence of power-to-gas.

Demand from datacentres makes up a rapidly growing portion of electricity demand in Ireland. Increased demand in turn gives rise to increased renewable generation, mandated by government targets, and a corresponding increase in subsidisation levels. The current method of apportioning renewable subsidy costs may lead to consumers other than datacentres bearing this excess cost of subsidisation. This letter calculates the expected impact on these consumers.

Efficient renewables deployment requires the minimisation of both internal generation costs and external transmission expansion planning (TEP) costs. Competitive pay-as-bid connection auctions allow wind energy generators to reveal their costs of generation such that internal generation costs may be minimised. TEP costs have not been incorporated into such auctions to date. Integrating these procedures may allow for a global minimisation of internal generation and external TEP costs over many time periods. This paper develops an auction mechanism and associated modelling framework to carry this out. The contributions of this framework are verified using a numerical example. Our results show that ignoring generation costs in transmission expansion planning has quantifiable economic consequences, while traditional pay-as-bid auctions can benefit from incorporating features associated with TEP, such as multi-period optimisation. Full integration of both modelling frameworks leads to efficiency improvements, both in terms of reduced investor rentseeking and a more efficient deployment path.

As a result of government policies increasing the amount of electricity generated from fluctuating renewable sources in many countries, the requirement for flexibility in the corresponding electricity systems increases. On the demand side, load shedding is one demand response mechanism contributing to an increased flexibility. Traditionally, load shedding was based on rather static or rotational strategies, whereby the system operator chooses the consumers for load shedding. However, ongoing technological developments provide the basis for smarter and more efficient load shedding strategies. We therefore examine the costs and strategies associated with such mechanisms by modelling an electricity market with different types of generators and consumers. Some consumers provide flexibility through load shedding only while others additionally have the ability to generate their own electricity. Focusing on the impacts of how and to whom consumers with own generation ability can supply electricity, the presence of market power and generator uncertainty we propose a rolling horizon stochastic mixed complementarity equilibrium model, where the individual optimisation problems of each player are solved simultaneously and in equilibrium. We find that a non-static strategy reduces consumer costs while allowing consumers to provide own generation to the whole market results in minimal benefits. The presence of market power was found to increase costs to consumers. We also consider the optimal foresight horizon that market players should consider. This novel study finds that the optimal foresight horizon is mainly driven by the daily load structure and, to a lower degree, by the uncertainty of the generators' availability.

Liberalised electricity markets often include a capacity remuneration mechanism to allow generation firms recover their fixed costs. Various de-rating factors and/or penalties have been incorporated into such mechanisms in order to award the unit based on the contribution they make to system security, which in turn depends on the unit's reliability. However, this reliability is known to the firm but not to the regulator. We propose an adaptation of menu regulation to design capacity payments based on a declaration by the firm of their reliability. We scale payments and penalties according to this declared reliability such that the firm's profit-maximising strategy is to truthfully reveal their reliability. We apply the methodology to an illustrative test system. Truth-telling is induced, increasing the efficiency of capacity payments while eliminating the requirement for the regulator to allocate resources to discovering reliability.

Renewable energy deployment costs comprise both internal generation costs and external locationrelated infrastructure, environmental and social costs. To minimise generation costs, competitive connection contract auctions are becoming increasingly common. Should external costs have considerable influence on site selection outside of the auction process, optimal bidding strategies may be affected by the resulting re-ranking of winning bids. This paper elicits the impact this may have on optimal bidding behaviour. Specifically, we address the impact internalisation of external costs may have on bidding strategy. With deterministic generation costs, optimal bidding strategies include a markup. The optimal markup is lower if external costs are internalised into the investment decision. If investors have the ability to appropriate rents, due to market dominance or asymmetric information, non-internalised external costs lower markup. Generation cost uncertainty may result in below-cost bidding. This is less likely when externalities are not internalised. For markets where bids are competitively priced, this paper provides evidence to suggest that methods to minimise externalities associated with renewables deployment should be integrated with competitive pay-as-bid auctions.

Capacity remuneration mechanisms exist in many electricity markets. Capacity mechanism designs do not explicitly consider the effects of refurbishment of existing generation units in order to increase their reliability. This paper presents a mixed complementarity problem with endogenous probabilities to examine the impact of refurbishment on electricity prices and generation investment. Capacity payments are found to increase reliability when refurbishment is not possible, while capacity payments and reliability options yield similar results when refurbishment is possible. Final costs to consumers are similar under the two mechanisms with the exception of the initial case of overcapacity.