alefunxo

Basopra

BASOPRA - BAttery Schedule OPtimizer for Residential Applications. Daily battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute temporal resolution are used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.

BASOPRA_FC

BASOPRA_HP

Daily EV battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute, 30-minute and 1-hour temporal resolution may be used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.

Complementarity-Wind-PV

Script and data used for the article Embracing wind power in the solar PV-dominated Swiss landscape

github-pages-with-jekyll

HP-modelling

multi-objectivePVHP

The first paper will focus on the multi-criteria optimization (cost, CO2) at the local level with a comparative Pareto analysis of housings with different consumption patterns and the respective merits of PV+battery systems; ideally, it would be good if we do get a hold of data of electricity consumption for housings which have heat pumps as heating systems (specially in Switzerland given the trend), as this would make two very distinct clusters besides other parameters such as behavioral aspects that could lead to the identification of different consumption patterns.

notebook

Jupyter Interactive Notebook

P2P-communities-PV-Battery

Solar_communities

Project developed in order to include the user preferences in the charging and discharging of the battery. We use a deterministic approach and include probabilities to discharge the battery to the grid in the frame of a community with P2P energy trading.

alefunxo/Basopra

BASOPRA - BAttery Schedule OPtimizer for Residential Applications. Daily battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute temporal resolution are used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.

alefunxo/P2P-communities-PV-Battery

alefunxo/BASOPRA_HP

Daily EV battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute, 30-minute and 1-hour temporal resolution may be used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.

alefunxo/Solar_communities

Project developed in order to include the user preferences in the charging and discharging of the battery. We use a deterministic approach and include probabilities to discharge the battery to the grid in the frame of a community with P2P energy trading.

alefunxo/BASOPRA_FC

alefunxo/Complementarity-Wind-PV

Script and data used for the article Embracing wind power in the solar PV-dominated Swiss landscape

alefunxo/github-pages-with-jekyll

alefunxo/HP-modelling

alefunxo/multi-objectivePVHP

The first paper will focus on the multi-criteria optimization (cost, CO2) at the local level with a comparative Pareto analysis of housings with different consumption patterns and the respective merits of PV+battery systems; ideally, it would be good if we do get a hold of data of electricity consumption for housings which have heat pumps as heating systems (specially in Switzerland given the trend), as this would make two very distinct clusters besides other parameters such as behavioral aspects that could lead to the identification of different consumption patterns.

alefunxo/notebook

Jupyter Interactive Notebook