TY - GEN A1 - Mechleri, Evgenia A1 - Sidnell, Tim A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Optimisation and control of a distributed energy resource network using Internet-of-Things technologies T2 - Computer Aided Chemical Engineering N2 - This work investigates the use of variable pricing to control electricity imported and exported to and from both fixed and unfixed distributed energy resource network designs within the UK residential sector. It was proven that networks which utilise much of their own energy and import little from the national grid are barely affected by variable import pricing, but are encouraged to export more energy to the grid by dynamic export pricing. Dynamic import and export pricing increased CO2 emissions due to feed-in tariffs which encourages CHP generation over lower-carbon technologies such as solar panels or wind turbines. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/abs/pii/B978012818634350014X?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-818634-3.50014-X SN - 1570-7946 VL - 46 SP - 79 EP - 84 ER - TY - GEN A1 - Sidnell, Tim A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Effects of Dynamic Pricing on the Design and Operation of Distributed Energy Resource Networks T2 - Processes N2 - This paper presents a framework for the use of variable pricing to control electricity im-ported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the national grid, are barely affected by dynamic import pricing, but are encouraged to sell more by dynamic export pricing. An increase in CO2 emissions per kWh of energy produced is observed for dynamic import and export, against a baseline configuration utilizing constant pricing. This is due to feed-in tariffs (FITs) that encourage CHP generation over lower-carbon technologies. Furthermore, batteries are shown to be expensive in systems receiving income from FITs and grid exports, but for the cases when they sell to/buy from the grid using dynamic pricing, their use in the networks becomes more economical. Keywords: distributed energy resource (DER); dynamic pricing; mixed-integer linear programming (MILP); renewable heat incentive (RHI); feed-in tariff (FIT); electricity storage in batteries. Y1 - 2021 UR - https://www.mdpi.com/2227-9717/9/8/1306 U6 - https://doi.org/https://doi.org/10.3390/pr9081306 SN - 2227-9717 VL - 9 IS - 8 ER - TY - GEN A1 - Sidnell, Tim A1 - Clarke, Fiona A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Optimal design and operation of distributed energy resources systems for residential neighbourhoods T2 - Smart Energy N2 - Different designs of distributed energy resources (DER) systems could lead to different performance in reducing cost, environmental impact or use of primary energy in residential networks. Hence, optimal design and management are important tasks to promote diffusion against the centralised grid. However, current operational models for such systems do not adequately analyse their complexity. This paper presents the results of a mixed-integer linear programming (MILP) model of distributed energy systems in the residential sector which builds up on previous work in this field. A superstructure optimisation model for design and operation of DER systems is obtained, providing a more holistic overview of such systems by including the following novel elements: a) Design and utilisation of a network with integrated heating/cooling pipelines and microgrid connections between neighbourhoods; b) Exploration of use of feed-in tariffs (FITs), renewable heat incentives (RHIs) and the ability to buy/sell from/to the national grid. It is shown that the (DER network mitigates around 30–40% of the CO2 emissions per household, compared with “traditional generation”. Money from FITs, RHIs and sales to the grid, as well as reduced grid purchases, make DER networks far more economical, and even profitable, compared to the traditional energy consumption. Y1 - 2021 UR - https://www.sciencedirect.com/science/article/pii/S2666955221000496?via%3Dihub U6 - https://doi.org/10.1016/j.segy.2021.100049 SN - 2666-9552 VL - 4 ER -