• Energy Research

This paper presents the main objectives, approach, results and challenges achieved so far of the H2020 project PANTERA (PAN European Technology Energy Research Approach). A special highlight of the work carried out in the Balkan region considering the first PANTERA workshop in Sofia, Bulgaria is given. Based on analysis of the results achieved, the potential for improvements and future steps are elaborated.

Power systems are operated to deliver electricity at minimum cost while adhering to operational and technical constraints. The introduction of smart grid technologies and renewable energy sources offers new challenges and opportunities for the efficient and reliable management of the grid. In this paper we focus on a Mixed Integer Programming sub-hour Unit Commitment model. We present analysis of computational results from a large set of problem instances based on the Irish system and show that problem instances with higher variability in net demand (after the integration of renewables) are more challenging to solve

Abstract Smart metering in electricity markets offers an opportunity to explore more diverse tariff structures. In this article a Genetic Algorithm (GA) is used to design Time of Use tariffs that minimise the wholesale risk to the supplier in residential markets. Residential demand and the System Marginal Price of Ireland's Single Electricity Market are simulated to estimate the wholesale risk associated with each tariff.

Demand-Side Management systems aim to modulate energy consumption at the customer side of the meter using price incentives. Current incentive schemes allow consumers to reduce their costs, and from the point of view of the supplier play a role in load balancing, but do not lead to optimal demand patterns. In the context of charging fleets of electric vehicles, we propose a centralised method for setting overnight charging schedules. This method uses evolutionary algorithms to automatically search for optimal plans, representing both the charging schedule and the energy drawn from the grid at each time-step. In successive experiments, we optimise for increased state of charge, reduced peak demand, and reduced consumer costs. In simulations, the centralised method achieves improvements in performance relative to simple models of non-centralised consumer behaviour.

Community energy projects have gained popularity in recent years, and encouraging citizens to form local energy communities (LEC) is considered an effective tool for raising awareness about renewable energy. Since no single universal method exists for operating LECs, this study investigated the impact that different business models and asset dispatch methods have on LECs’ economic and energy-related indicators. We carried out a case study, which included the development, modelling, and simulation of seven scenarios using mixed-integer linear programming (MILP). To measure and compare the prospective performance of the LECs in each scenario, six key metrics were evaluated and assessed. The authors find that simple, rule-based control systems might be well suited for LECs with a limited number of controllable assets that aim to provide increased levels of self-consumption of up to 3%. We also conclude that when the LEC utilises an energy cooperative business model, the selected asset dispatch method provides only minor differences in LEC performance, while for prosumer communities, the importance of selecting a suitable asset dispatch method is higher. We also conclude that LECs have the potential to significantly increase their economic performance by more than 10% by acting as aggregators and providing grid services directly to system operators.

Renewable and local energy communities are viewed as a key component to the success of the energy transition. In this paper, we estimate wind power potential for such communities. Acquiring the most accurate weather data is important to support decision-making. We identify the most reliable publicly available wind speed data and demonstrate a case study for typical energy community scenarios such as a single commercial turbine at coastal and inland locations in Ireland. We describe our assessment methodology to evaluate the quality of the wind source data by comparing it with meteorological observations. We make recommendations on which publicly available wind data sources, such as reanalysis data sources (MERRA-2, ERA-5), PVGIS, and NEWA are best suited to support Renewable Energy Communities interested in exploring the possibilities of renewable wind energy. ERA5 is deemed to be the most suitable wind data source for these locations, while an anomaly is noted in the NEWA data.

This paper explores gender dimensions of the energy transition in the European Union (EU). The EU has set out its ambitions for an equitable transition to clean secure energy. It has also set out it objectives for gender equality. In this paper, I implement a systematic literature review to explore the intersection of gender issues with the energy transition in the EU. There is little peer reviewed literature in this area. Analysis of academic papers shows most focus on social science rather than technical or engineering problems. A critical review of the grey literature including EU policies and reports shows that there is a disconnect between EU gender equality and clean energy plans and that gender has yet to be mainstreamed into the EU energy transition. This review identifies opportunities to mainstream gender into EU energy policies by linking to EU gender equality objectives, and connecting to gender-energy research themes.