Eduardo A. Martínez Ceseña

Flexible Distributed Multienergy Generation System Expansion Planning Under Uncertainty

Summary form only given. A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems.

Distribution network capacity support from flexible smart multi-energy districts

This paper explores from a techno-economic perspective the value of increasing distribution network capacity via Demand Side Response (DSR) services provided by smart multi-energy systems enabled by an intelligent information platform (i.e., the District Information Modelling and Management for Energy Reduction (DIMMER) platform under development in the homonymous European project). More specifically, the potential of smart multi-energy systems comprising gas boilers, Electric Heat Pumps (EHP) Combined Heat and Power (CHP) and a smart information platform to provide distribution network capacity is explored. For this purpose, a multi-energy district operation optimization approach coupled with a distribution network planning framework is proposed. The district operation model identifies the behavior of end-users who may aim at minimizing their energy costs and/or trade capacity with DNOs. The network planning framework calculates the value for DNOs from additional network capacity provided by customers. The methodology is illustrated via a real UK multi-energy district at the University of Manchester and the relevant electricity, heat and gas networks. The results highlight that the flexibility inherent in multi-energy systems can provide significant economic benefits for both end-users and DNOs.

Smart distribution networks, demand side response, and community energy systems: Field trial experiences and smart grid modeling advances in the United Kingdom

Abstract Emerging smart grid solutions are perhaps the most attractive options to meet the ever-increasing needs for economic, reliable, sustainable, and socially acceptable energy production and consumption in the United Kingdom. In particular, smart solutions are vital to cater to the integration of economic and low carbon distributed energy resources (DERs) at the community level. However, there is still little understanding of how to effectively use DERs in bringing about benefits for the energy system or enhance distribution networks to enable the smart operation of DERs. This chapter presents the latest UK research in smart grid applications and distribution networks and how intelligent community energy systems are enabled by DERs. Results from several British and European projects involving trials in UK networks and communities are presented. It is demonstrated that new and more intelligent tools are needed to deploy and use smart solutions properly.

Flexible distributed multienergy generation system expansion planning under uncertainty

A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems.