Abstract

Procedural generation of urban environments is a very difficult problem to solve. Most solutions use predefined production rules which lock them into only few different variations of the result. This works well when producing new urban environments but fails when it comes to the expansion of them. Most cities are too complex to model using an approach which utilises predefined rules. By using an example based approach instead, it is possible to expand any city and still have the new street network follow the layout of the original city, regardless of complexity. This paper describes a method of extracting the necessary information from the GIS database OpenStreetMap and expanding the cities using an example based approach presented by Aliaga et al. The paper will also show how blocks, parcels and buildings can be generated to fit within the urban environment.

Abstract

Energy supply through integrated renewable energy sources (RESs) and battery systems will be of higher importance for future residential sectors. Optimal energy management and sizing for the components of residential systems can enhance efficiency, self-suffiency, and meanwhile can be cost-effective by reducing investment as well as operating costs. Accordingly, this paper proposes an exhaustive optimization model for determining the capacity of RESs, namely: wind turbines and photovoltaic (PV) systems. In this study, batteries and electric vehicles (EVs) are utilized in line with other sources to capture fluctuations of RESs. To model the uncertainties of RESs, energy prices, and load demands a linearized stochastic programming framework is applied. The proposed framework involves long-term and efficient resource development alongside with short-term management and utilization of these resources for supplying the demand load. In our study, we utilize the roulette wheel mechanism (RWM) method as well as proper probability distribution functions (PDFs) to generate scenarios for all sources of uncertainties, including wind turbines, PV systems, demand, and electricity market price. The approach is verified in two different cases, including an individual home and a larger micro-grid (MG). The results of multiple numerical simulations demonstrate the effectiveness of the proposed stochastic model.

Abstract

Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. However, effectiveness and usefulness of storage may vary under different circumstances. This study provides an abstract perspective on the merits of electrical energy storage integrated with decentralized supply systems consisting of solar PV and wind power in a mesolevel, residential sector context. We used a balancing model to couple demand and supply patterns based on Dutch weather data and assess the resultant loads given various scenarios. Our model results highlight differences in storage effectiveness for solar PV and wind power, and strong diminishing-returns effects. Small storage capacities can be functional in reducing surpluses in overdimensioned supply systems and shortages in under-dimensioned supply systems. However, full elimination of imbalance requires substantial storage capacities. The overall potential of storage to mitigate imbalance of variable renewable energy is limited. Integration of storage in local supply systems may have self-sufficiency and cost-effectiveness benefits for prosumers but may have additional peak load disadvantages for grid operators. Adequate policy measures beyond current curtailment strategies are required to ensure proper distribution of benefits and responsibilities associated with variable renewable energy and storage.

Abstract

Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. However, effectiveness and usefulness of storage may vary under different circumstances. This study provides an abstract perspective on the merits of electrical energy storage integrated with decentralized supply systems consisting of solar PV and wind power in a mesolevel, residential sector context. We used a balancing model to couple demand and supply patterns based on Dutch weather data and assess the resultant loads given various scenarios. Our model results highlight differences in storage effectiveness for solar PV and wind power, and strong diminishing-returns effects. Small storage capacities can be functional in reducing surpluses in overdimensioned supply systems and shortages in under-dimensioned supply systems. However, full elimination of imbalance requires substantial storage capacities. The overall potential of storage to mitigate imbalance of variable renewable energy is limited. Integration of storage in local supply systems may have self-sufficiency and cost-effectiveness benefits for prosumers but may have additional peak load disadvantages for grid operators. Adequate policy measures beyond current curtailment strategies are required to ensure proper distribution of benefits and responsibilities associated with variable renewable energy and storage.