Agent-based simulation of electricity markets: a literature review

Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets. --

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

The merit-order effect: a detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany

The German feed-in support of electricity generation from renewable energy sources has led to high growth rates of the supported technologies. Critics state that the costs for consumers are too high. An important aspect to be considered in the discussion is the price effect created by renewable electricity generation. This paper seeks to analyse the impact of privileged renewable electricity generation on the electricity market in Germany. The central aspect to be analysed is the impact of renewable electricity generation on spot market prices. The results generated by an agent-based simulation platform indicate that the financial volume of the price reduction is considerable. In the short run, this gives rise to a distributional effect which creates savings for the demand side by reducing generator profits. In the case of the year 2006, the volume of the merit-order effect exceeds the volume of the net support payments for renewable electricity generation which have to be paid by consumers. --

A CGE-Analysis of Energy Policies Considering Labor Market Imperfections and Technology Specifications

The paper establishes a CGE/MPSGE model for evaluating energy policy measures with emphasis on their employment impacts. It specifies a dual labor market with respect to qualification, two different mechanisms for skill specific unemployment, and a technology detailed description of electricity generation. Non clearing of the dual labor market is modeled via minimum wage constraints and via wage curves. The model is exemplarily applied for the analysis of capital subsidies on the application of technologies using renewable energy sources. Quantitative results highlight that subsidies on these technologies do not automatically lead to a significant reduction in emissions. Moreover, if emission reductions are achieved these might actually partly result from negative growth effects induced by the promotion of cost inefficient technologies. Inefficiencies in the energy system increase unemployment for both skilled and unskilled labor.CGE, Energy Economic Analysis, Employment Impact, Choice of Technology

The Merit-Order Effect of Load-Shifting: An Estimate for the Spanish Market

Renewable producers can offer selling bids with very low marginal cost since they are not obliged to include on any cost related to the use of energy from the wind or sun. Accordingly, when the Market Operator integrates a renewable bid in the merit-order generation curve, all the generators based on conventional technologies, with higher marginal cost due to the cost of fuels, are displaced to the right. The right-shifting of the merit-order generation curve leads to a lower clearing price, a small increment of the traded energy (almost inelastic demand curve), and a reduction of the total cost of the energy traded in the wholesale market. This is the key mechanism of the well-known merit-order effect of renewables. Load-shifting (demand-side management) plans are expected to yield a reduction of the cost of the traded energy for the customers, since the cost-saving due to the energy eschewed at peak hours would be greater than the extra cost due to the increased demand at off-peak hours. This work will show that the main effects of load-shifting on the market are qualitatively similar to that of renewables, which exemplify the existence a “merit-order effect of load-shifting”. To analyse the characteristics of the merit-order effect of load-shifting, a simplified model has been developed, based on the displacement of the generation and demand curves. A set of scenarios has been generated in order to quantify the main effects on the Spanish/Iberian market for 2015.Ministerio de Economía y Competitividad, España (Ministry of Economy and Competitiveness, Spain) grant ENE2016-77650-

New market designs in electricity market simulation models: Deliverable D4.5

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: To integrate a high share of renewables in a future system, several modifications to the electricity market rules may need to be implemented. The most relevant market design concepts were identified from the literature and reported in work package 3. There are several uncertainties, for instance with respect to the questions of whether a future electricity market will provide enough incentives for investment in variable renewable energy sources (vRES) – mainly solar and wind energy – and in flexibility options, especially for long periods with insufficient vRES generation. In this deliverable, the modelling requirements to analyse the new market rules are determined. The modelling efforts will reflect the main policy choices and are based on the strengths of the modelling capabilities from the consortium. The model enhancements to represent the temporal, spatial and sectoral flexibility will be approached in deliverables 4.1 to 4.3. For this reason, these topics will be described only briefly in this deliverable.N/

Modelling the future development of renewable energy technologies in the European electricity sector using agent-based simulation

Increasing the share of renewable energy sources in final energy consumption forms an important part of the EU\u27s energy and climate strategy. An agent-based simulation model is developed to assess future diffusion processes of renewable energy technologies under different policy regimes. The developed model helps to design support policies, or point out existing investment opportunities for interested stakeholders

Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C

Whole-economy scenarios for limiting global warming to 1.5C suggest that direct carbon emissions in the buildings sector should decrease to almost zero by 2050, but leave unanswered the question how this could be achieved by real-world policies. We take a modelling-based approach for simulating which policy measures could induce an almost-complete decarbonisation of residential heating, the by far largest source of direct emissions in residential buildings. Under which assumptions is it possible, and how long would it take? Policy effectiveness highly depends on behavioural decision- making by households, especially in a context of deep decarbonisation and rapid transformation. We therefore use the non-equilibrium bottom-up model FTT:Heat to simulate policies for a transition towards low-carbon heating in a context of inertia and bounded rationality, focusing on the uptake of heating technologies. Results indicate that the near-zero decarbonisation is achievable by 2050, but requires substantial policy efforts. Policy mixes are projected to be more effective and robust for driving the market of efficient low-carbon technologies, compared to the reliance on a carbon tax as the only policy instrument. In combination with subsidies for renewables, near-complete decarbonisation could be achieved with a residential carbon tax of 50-200Euro/tCO2. The policy-induced technology transition would increase average heating costs faced by households initially, but could also lead to cost reductions in most world regions in the medium term. Model projections illustrate the uncertainty that is attached to household behaviour for prematurely replacing heating systems