Alejandro Navarro-Espinosa

Probabilistic Impact Assessment of Low Carbon Technologies in LV Distribution Systems

Residential-scale low carbon technologies (LCTs) can help decarbonizing our economies but can also lead to technical issues, particularly in low voltage (LV) distribution systems. To quantify these problems this work proposes a probabilistic impact assessment methodology. First, realistic 5-min time-series daily profiles are produced for photovoltaic panels, electric heat pumps, electric vehicles, and micro combined heat and power units. Then, to cater for the uncertainties of LCTs (e.g., size, location, and behavior), a Monte Carlo analysis is carried out considering 100 simulations for different penetration levels (percentage of houses with a LCT). This methodology is applied to 128 real U.K. LV feeders showing that about half of them can have voltage and/or congestion issues at some penetration of LCTs. Furthermore, to identify the relationships between the first occurrence of problems and key feeder parameters (e.g., length, number of customers), a correlation analysis is developed per LCT. Crucially, these results can be translated into lookup tables to help distribution network operators in producing preliminary estimates of the LCT hosting capacity of a given feeder.

Assessing the benefits of PV var absorption on the hosting capacity of LV feeders

The UK has reached, thanks to the Feed-In-Tariff scheme, an installed photovoltaic (PV) capacity of almost 1.5GW mostly connected to low voltage (LV) networks. Voltage rise issues have started to appear particularly in clusters of PV systems. Thus, in order to defer potential network reinforcements, Distribution Network Operators have to consider alternative solutions that can cost-effectively allow hosting the ongoing and future uptake of PV systems. Adopting a thorough Monte Carlo-based analysis, this work evaluates the potential benefits from using the power factor capabilities of PV systems connected to LV feeders. The results, based on a real UK suburban LV feeder, show that for a given penetration level, the number of customers affected by voltage issues at a given penetration level can be significantly reduced when adopting PV reactive power absorption. However, this strategy had a limited effect on the reduction of the overall voltage rise issue.

Increasing the PV hosting capacity of LV networks: OLTC-fitted transformers vs. reinforcements

The increasing adoption of domestic-scale photovoltaic (PV) systems in the UK is likely to bring significant technical voltage rise issues in low voltage (LV) networks. This work investigates the techno-economic benefits from using onload tap changers (OLTC)-fitted transformers to cope with high penetrations of PV. Two voltage regulation approaches are considered: local (busbar) and remote (furthest point). Results are contrasted with traditional network reinforcements. High resolution profiles for residential load and PV systems are used on a real UK LV network. The findings show that the OLTC-fitted transformer increases the hosting capacity of the network. The remote approach combined with adequate OLTC design performs better than the local one but the former is only needed for high penetration levels (from 70%). Finally, it is shown that the reinforcement alternative is more cost-effective for smaller penetration levels (up to 60%) in the network studied and for current prices.

Physical modeling of electro-thermal domestic heating systems with quantification of economic and environmental costs

Electro-thermal domestic heating systems represent excellent potential sources for demand response and demand side flexibility given the large amount of storage inherent in them. However, they must be modeled using an approach which adequately captures the detailed physics of the problem (in order to properly assess the different sources of inherent storage), and yet is simple enough to be generalizable to any building and heating type that could be available in the future. This paper presents a comprehensive physical modeling approach for electro-thermal domestic heating systems, in which space heating demand derived from the physical modeling approach is combined with domestic hot water and electricity demand to demonstrate how quantification of economic and environmental costs of different domestic heating systems as well as of the thermal inertia of different components (for future demand response studies) may be undertaken.

Representative Residential LV Feeders: A Case Study for the North West of England

The adoption of residential-scale low carbon technologies, such as photovoltaic panels or electric vehicles, is expected to significantly increase in the near future. Therefore, it is important for distribution network operators (DNOs) to understand the impacts that these technologies may have, particularly, on low voltage (LV) networks. The challenge, however, is that these LV networks are large in number and diverse in characteristics. In this work, four clustering algorithms (hierarchical clustering, k- medoids++, improved k- means++, and Gaussian Mixture Model-GMM), are applied to a set of 232 residential LV feeders from the North West of England to obtain representative feeders. Moreover, time-series monitoring data, presence of residential-scale generation, and detailed customer classification are considered in the analysis. Multiple validity indices are used to identify the most suitable algorithm. The improved k- means++ and GMM showed the best performances resulting in eleven representative feeders with prominent characteristics such as number and type of customers, total cable length, neutral current, and presence of generation. Crucially, the results from studies performed on these feeders can then be extrapolated to those they represent, simplifying the analyses to be carried out by DNOs. This is demonstrated with a hosting capacity assessment of photovoltaic panels in LV feeders.

Assessing the benefits of meshed operation of LV feeders with low carbon technologies

Significant penetrations of low carbon technologies in low voltage (LV) networks could result in voltage issues, thermal overloads of the lines, higher energy losses, etc. In this work, the meshed connection of LV feeders is investigated as one of the possible alternatives to minimise these impacts and, consequently, increase the corresponding hosting capacity. Two different technologies, photovoltaic panels (PV) and electric heat pumps (EHP) are studied for different penetration levels by using a real three-phase four-wire LV network in the North West of England. Profiles of loads, PV and EHP have a granularity of 30 minutes. Energy losses, voltage problems and thermal loading are studied. A Monte Carlo approach is considered in order to cater for the random nature of some parameters such as the location and size of low carbon technologies. Results for the studied LV network clearly indicate that meshed operation can indeed increase its ability to host higher penetrations of PV and EHP.

Participation of electric heat pump resources in electricity markets under uncertainty

This paper presents a model for calculating the optimal purchasing strategy in a day ahead market for an aggregation of domestic buildings utilising electric heat pumps (EHP) to supply low grade thermal energy (for space heating and domestic hot water). The model includes physical models of buildings and of thermal energy stores (TES). Uncertainty in outdoor temperature (hence space heating demand and imbalance volume) and imbalance prices is modelled using a stochastic programming approach, whilst uncertainty in non-heating electricity and domestic hot water demand, and building occupancy (which is a determinant of space heating demand) is accounted for through random assignation of synthetic profiles to buildings/scenarios. The effect on the purchasing costs of the presence and size of a TES and the effect of the size of the EHP are tested.

EHP in low voltage networks: Understanding the effects of heat emitters and room temperatures

The adoption of Electric Heat Pumps (EHPs) at residential level can support the decarbonization of domestic heating. However, these new loads can produce technical problems in low voltage (LV) distribution networks. This work studies the EHP technical impacts in LV feeders, analyzing potential actions to minimize them. Particularly, two cases are investigated: the utilization of different heat emitters and the selection of different indoor temperatures. These cases are explored by using a Monte Carlo approach to cater for the uncertainty of LV demand. Daily one-minute resolution profiles are adopted for the domestic energy consumption in each of the sensitivities considered. The methodology is applied on three real UK LV networks. Results show that the decrease in the set temperature leads to a small reduction in the likelihood of technical impacts, whereas the utilization of underfloor heating can significantly reduce the likelihood of such impacts, resulting in a higher EHP penetration.

On the cascading effects of residential-scale PV disconnection due to voltage rise

Photovoltaic penetration in LV networks can produce voltage rise above the limits, resulting in the automatic disconnection of panels. This voltage-driven disconnection of particularly single-phase PV panels combined with the unbalance nature of LV networks might produce a further voltage rise in one of the other phases. This can result in a new PV disconnection. This paper analyses to which extent the risk of PV cascading exists in LV networks. A 5-minute time-series power flow analysis is adopted using a real LV network (7 feeders and 346 customers) in the North West of England. The results indicate that the risk of cascading does exist. However, the proportion of cascading disconnections is likely to be small (although increases with PV penetration). Moreover, cascading disconnections happen mostly in the period after the first automatic disconnection(s). Consequently, the actual cascading nature is very limited.

Representative residential LV feeders: A case study for the North West of England

The adoption of residential-scale low carbon technologies, such as photovoltaic panels or electric vehicles, is expected to significantly increase in the near future. Therefore, it is important for distribution network operators (DNOs) to understand the impacts that these technologies may have, particularly, on low voltage (LV) networks. The challenge, however, is that these LV networks are large in number and diverse in characteristics. In this work, four clustering algorithms (hierarchical clustering, k-medoids++, improved k-means ++, and Gaussian Mixture Model-GMM), are applied to a set of 232 residential LV feeders from the North West of England to obtain representative feeders. Moreover, time-series monitoring data, presence of residential-scale generation, and detailed customer classification are considered in the analysis. Multiple validity indices are used to identify the most suitable algorithm. The improved k-means++ and GMM showed the best performances resulting in eleven representative feeders with prominent characteristics such as number and type of customers, total cable length, neutral current, and presence of generation. Crucially, the results from studies performed on these feeders can then be extrapolated to those they represent, simplifying the analyses to be carried out by DNOs. This is demonstrated with a hosting capacity assessment of photovoltaic panels in LV feeders.