C.F. Calvillo

Distributed energy generation in smart cities

The smart city is a sustainable and efficient urban center that provides high quality of life to its inhabitants with an optimal management of its resources, where clean and cost effective energy generation is a key issue. Under this setting, distributed generation can provide an adequate tool to deal with energy reliability and to successfully implement renewable sources; nevertheless, selection and scaling of energy systems, considering location, is not a trivial task. Frequently, the stakeholders analyze only one or two “popular” generation systems, and then calculate the output and return of investment in a simplified and approximated approach. This practice could lead the stakeholder to an inadequate technology mix. To tackle this problem, this paper reviews and models most common energy sources for distributed generation in a smart city context. Then, a technical economic analysis is developed for 2 cases, a household and a district, considering not only renewable sources but also efficient non-renewable technologies. The results of the numerical analysis help to assess the more adequate generation systems for a given application, energetic demand, and geographical characteristics. A well-developed analysis is essential for a better understanding of the available technologies and their synergies; as a result, the investors can choose the appropriate solutions, maximizing overall benefits.

Business Models Towards the Effective Integration of Electric Vehicles in the Grid

To achieve an effective integration of the electric vehicle in the grid, not only technical issues must be solved, but also a new regulatory context and business models must be proposed. This paper proposes two electric vehicle integration business models; one resembles the mobile-phone business, while the other is more based on current practices in the electricity-supply business. Decomposition into three layers: physical, management, and business, is used to describe those business models. Furthermore, electric vehicle charging scenarios are presented to illustrate how the proposed business models fit in each of the potential situations. Finally, several practical study cases are presented.

Evaluation and optimal scaling of distributed generation systems in a smart city

Distributed generation (DG) represents an important resource to address relevant energy issues, such as reliability and sustainability, in the current and future smart cities. It is expected that distributed generation will gain considerable presence in the following years; however, the selection and sizing of the generation and storage systems is commonly done without an adequate level of detail. This simplified or approximated approach usually results in a suboptimal technology mix with an inadequate type of system and/or scale, which could compromise the economic feasibility of the DG project. To tackle this problem, stakeholders should consider many factors, including geographical characteristics (sun, wind …), energy costs, local regulation, and energetic demand patterns, apart from analysing different technologies. Considering as an example location the city of Madrid, Spain, this paper proposes a linear programming model to evaluate the most common distributed generation technologies, with and without storage systems and under different electricity pricing scenarios. As a result, not only the optimal sizing, but also the optimal operation scheduling of the aforementioned systems are found. Then, an economic feasibility analysis is developed, comparing the different technologies and defining the best option for a given scenario. Furthermore, this study helps to find important milestones, such as battery prices, that could make distributed generation more attractive.

Price-maker optimal planning and operation of distributed energy resources

This paper proposes a linear programming problem to find the optimal planning and operation of aggregated distributed energy resources (DER), managed by an aggregator that participates in the day-ahead wholesale electricity market as a price-maker agent. The proposed model analyzes the impact of the size of the aggregated resources and gives the optimal planning and management of DER systems, and the corresponding energy transactions in the wholesale day-ahead market. The results suggest that when the aggregated resources are large enough, DER systems can achieve up to 32% extra economic benefits depending on the market share, compared with a business-as-usual approach (not implementing DER systems).

Use of Renewable Energy Systems in Smart Cities

Renewable energy sources (RES) used in small-scale distributed generation systems are a promising alternative for additional energy supply toward smarter and more sustainable cities. However, their proper integration as new infrastructures of the smart city (SMCT) requires understanding the SMCT architecture and promoting changes to the existing regulation, business models, and power grid topology and operation, constituting a new challenging energy supply paradigm. This chapter addresses the use of renewable energy systems on small scale, oriented to distributed generation (DG) for households or districts, integrated in an SMCT. In this context, the main renewable energies and companion technologies are reviewed, and their profitability investigated to highlight their current economic feasibility. A simplified architecture for SMCT development is presented, consisting of three interconnected layers, the intelligence layer, the communication layer, and the infrastructure layer. The integration and impact of distributed renewable energy generation and storage technologies in this architecture is analyzed. Special attention is paid to the grid topology for their technical and efficient integration, and to the business models for facilitating their economic integration and feasibility.

Vehicle-to-grid profitability considering EV battery degradation

The electrification of the transportation sector is likely to contribute reducing the global dependency on oil and is expected to drive investments to renewable and intermittent energy sources, by taking advantage of it energy storage capacity. In order to facilitate the EV integration to the grid, and to take advantage of the battery storage and the Vehicle-to-Grid (V2G) scheme, smart charging strategies will be required. However, these strategies rarely consider all relevant costs, such as battery degradation. This work analyses the profitability of bidirectional energy transfer, i.e. the possibility of using aggregated EV batteries as storage for energy which can be injected back to the grid, by considering battery degradation as a cost included in the proposed strategy. A mixed integer linear problem (MILP) for minimizing energy costs and battery ageing costs for EV owners is formulated. The battery degradation due to charging and discharging in the V2G scheme is accounted for in the model used. Two case studies of overnight charging of EVs in Sweden and in Spain are proposed. Results show that given current energy prices and battery costs, V2G is not profitable for EV owners, but if battery prices decrease as expected, the V2G will be present in the medium term.

Optimal planning and operation of distributed energy resources considering uncertainty on EVs

Operation of distributed energy resources is taking importance nowadays. This paper proposes an optimal planning and operation model of distributed energy resources in a district taking into account the mobility of consumers using conventional fuel vehicles (FV) or electric vehicles (EV). The stochastic model considers the uncertainty of the type of vehicle, availability and distance traveled, and then it manages the available resources to obtain the maximum benefit from the grid. Results show that the EVs assist to achieve greater benefits of the distributed resources. Moreover, the costs per driven km are mainly independent of the type of vehicle considered.