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This briefing paper This paper outlines the challenges for modelling local and regional energy systems and assesses the capabilities of selected UKERC energy system models, with a focus on interactions between national and local energy systems.

Governments' net zero emission target aims at increasing the share of renewable energy sources as well as influencing the behaviours of consumers to support the cost-effective balancing of energy supply and demand. These will be achieved by the advanced information and control infrastructures of smart grids which allow the interoperability among various stakeholders. Under this circumstance, increasing number of consumers produce, store, and consume energy, giving them a new role of prosumers. The integration of prosumers and accommodation of incurred bidirectional flows of energy and information rely on two key factors: flexible structures of energy markets and intelligent operations of power systems. The blockchain and artificial intelligence (AI) are innovative technologies to fulfil these two factors, by which the blockchain provides decentralised trading platforms for energy markets and the AI supports the optimal operational control of power systems. This paper attempts to address how to incorporate the blockchain and AI in the smart grids for facilitating prosumers to participate in energy markets. To achieve this objective, first, this paper reviews how policy designs price carbon emissions caused by the fossil-fuel based generation so as to facilitate the integration of prosumers with renewable energy sources. Second, the potential structures of energy markets with the support of the blockchain technologies are discussed. Last, how to apply the AI for enhancing the state monitoring and decision making during the operations of power systems is introduced., Accepted by Renewable & Sustainable Energy Reviews on 21 Feb 2022

Climate change is higher on the agenda with the UK government raising the level of ambition, legislating for a net-zero target for all greenhouse gas emissions by 2050. This Review focuses on seven themes that form the backbone of UKERC’s research programme for the next five years. It sets out some of the challenges the government will face in reducing emissions – and makes specific recommendations about future policy priorities.

Accurate information regarding the uncertainty of short-term forecast for aggregate wind power is a key to efficient and cost effective integration of wind farms into power systems. This paper presents a methodology for producing wind power forecast scenarios. Using historical wind power time series data and the Kernel Density Estimator (KDE), probabilistic wind power forecast scenarios were generated according to a rolling process. The improvement achieved in the accuracy of forecasts through frequent updating of the forecasts taking into account the latest realized wind power was quantified. The forecast scenarios produced by the proposed method were used as inputs to a unit commitment and optimal dispatch model in order to investigate how the uncertainty in wind forecast affect the operation of power system and in particular gas-fired generators.

The aim of this project is to describe the expected evolution of the Spanish electricity sector in the coming decades, as well as to study the economic feasibility of solar PV and CCGT power generation plants in this context. First of all, an analysis of the Spanish electricity market has been carried out. The current energy situation has been also studied, both globally and nationally. Given the growing importance of renewable energies in the sector, the legislative development on renewables has been studied, as well as the impact they have generated in the sector and their different financing mechanisms. Based on the environmental objectives established by the European Union, the general lines of the expected energy transition in the Spanish electricity sector have been defined, estimating the installed capacity of the main generation technologies for the period 2020-2050, as well as their contribution in the generation mix. Likewise, an analysis of the price of electricity in the daily market has been carried out, from which a price prediction model has been developed. According to the results, the weight of renewables will increase progressively during the next decades, reaching in 2050 an approximate share of 90% in the generation mix. The expected load factor for CCGTs, on the other hand, will increase in the mid-term, whereas in the long-term will be reduced below the current values. The price of electricity, on the other hand, will increase significantly between 2020 and 2030, whereas as of this year will undergo a gradual but steady reduction. Given the expected relevance of solar PV and CCGT technologies in the future Spanish generation park, the economic feasibility of both technologies has been studied. In the case of the solar PV plant, an analytical model has been developed in MATLAB by which forecasts of the generation of the plant have been made. These results have been validated by the software SOLAR PV, making a comparison between both results. For the analysis of CCGT plant, the price in the adjustment markets has been studied, analysing its relationship with the price in the daily market. According to the results, both projects would be profitable. However, given the uncertainty inherent to forecasts of the price, alternative forecasts have been considered. Due to substantial differences in the mid-term, the main financial parameters of solar PV and CCGT power generation plants have been calculated again, considering in this case the alternative forecasts of the price. From this second analysis it has been concluded that, whereas the solar PV would not require any additional financing mechanism in order to be profitable, capacity payments would be indispensable in the case of the CCGT plant. It has been also concluded that, in the analysis of the economic feasibility of marginal technologies, such as CCGTs, the average price of the electricity in the markets is not a representative parameter. Outgoing