Abstract

The ambitious targets of the European Union (EU) for a greater penetration of renewable energy sources (RES) in all areas of activity have led to power systems with growing levels of variable RES (VRES) all over the EU. Considering these targets, the EU countries presented their National Energy and Climate Plans (NECP) with their expected capacity until 2030. The NECPs considered a relevant increase in the VRES capacity and in some cases a decrease in the capacity of dispatchable power plants. VRES have near-zero marginal costs and increase the volatility of the net-load due to the stochastic profile of their production. These characteristics increase the need to maintain fast-response dispatchable power plants to guarantee the security of supply and also decrease market prices. Thus, governments promote externalities, as capacity mechanisms and other incentives to these players, guaranteeing their economic sustainability. This study presents the optimization of the non-RES thermal capacity of the Iberian power system by 2030, considering the least-cost algorithm. Considering a cooperative scenario between Portugal and Spain, it is possible to reduce the system costs by 17.40%, the curtailments quantity by 21.93%, the number of market-splitting hours by 43.26% and the dioxide carbon emissions by 4.76%.

Highlights

  • Considering the Paris agreement, the European Union (EU) set ambitious targets to the majority penetration of renewable energy sources (RES) in all areas of activity, which has led to power systems with growing levels of variable RES (VRES) all over the EU

  • Are presented the four main methodologies behind the considered optimization of the power system: (i) the least-cost system, where the best mix of power plants to supply the demand at least-cost is obtained, (ii) power-plant bids are based on marginal costs, increasing the general welfare of the market participants, (iii) the levelized cost of energy (LCOE) of each technology, as a measure to compare the cost of each technology, and (iv) the levelized cash flow (LCF), used to compute the economic results of each technology

  • Marginal cost, and consumers will pay higher amounts for lower quantities of. This issue can be justified by the VRES strategies, that of having zero or near-zero marginal costs, and if they offer higher prices at spot markets they can be surpassed in the merit order effect, losing the opportunity of selling free-of-cost energy

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Summary

Introduction

Considering the Paris agreement, the European Union (EU) set ambitious targets to the majority penetration of renewable energy sources (RES) in all areas of activity, which has led to power systems with growing levels of variable RES (VRES) all over the EU. In this study the least-cost flexibility options to support these scenarios were obtained by considering an increase in demand response, electricity storage, interconnection capacity and curtailments, but they considered that gas-fired power plants with carbon capture and storage should replace some of the future RES capacity. This last solution may reduce the system costs by 12%, while electricity storage may slightly increase the system costs by 1%, and all other solutions only slightly reduce the system costs to 3%. Presents a least-cost optimization model with the goal of adapting the required thermal capacity to the RES penetration targets; Obtains the Iberian least-cost thermal mix by 2030 considering a reliable cooperation between Portugal and Spain, and compares it with the programmed scenario.

Power Systems Theory
Least-Cost System
Market
Levelized
Iberian Power Systems
Power Systems Data in the Iberian Peninsula
Demand
Power System Costs
Iberian Use of Each Thermal Technology in 2018
Iberian
Iberian Expected Use of Each Thermal Technology in 2030
GW and energy flexibility
The Optimal Iberian Power Systems
Optimal Iberian Power Systems in 2030
Optimal Iberian Power Systems in 2018
Sustainability of the Iberian Power Systems
Programmed Scenario
Cooperative Scenario
The Most Reliable Transition from 2018 to 2030
Findings
Final Remarks and Future Work
Full Text
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