Maximising revenue for non‐firm distributed wind generation with energy storage in an active management scheme

Abstract

The connection of high penetrations of renewable generation such as wind to distribution networks requires new active management techniques. Curtailing distributed generation during periods of network congestion allows for a higher penetration of distributed wind to connect, however, it reduces the potential revenue from these wind turbines. Energy storage can be used to alleviate this and the store can also be used to carry out other tasks such as trading on an electricity spot market, a mode of operation known as arbitrage. The combination of available revenue streams is crucial in the financial viability of energy storage. This study presents a heuristic algorithm for the optimisation of revenue generated by an energy storage unit working with two revenue streams: generation-curtailment reduction and arbitrage. The algorithm is used to demonstrate the ability of storage to generate revenue and to reduce generation curtailment for two case study networks. Studies carried out include a single wind farm and multiple wind farms connected under a 'last-in-first-out' principle of access. The results clearly show that storage using both operating modes increases revenue over either mode individually. Moreover, energy storage is shown to be effective at reducing curtailment while increasing the utilisation of circuits linking the distribution and transmission networks. Finally, renewable subsidies are considered as a potential third revenue stream. It is interesting to note that under current market agreements such subsidies have the potential to perversely encourage the installation of inefficient storage technologies, because of increased losses facilitating greater "utilisation" of renewable generation. reached the maximum capacity of firmly connected generation, for example, in the Orkney Isles [2]. An alternative management philosophy is Active Network Management (ANM) in which generators and other network components are managed in real time to reach specified goals. These techniques have been shown to be successful in managing voltage and thermal limits with increased distributed generation [3, 4]. Two applications of ANM are generation curtailment and the use of Energy storage systems (ESSs). Generation curtailment allows additional distributed generation to connect with the agreement that under specified network conditions the new generator may have to reduce output or disconnect entirely. A generation curtailment scheme is in operation on the Orkney distribution network [2] and manages thermal and voltage limits across the network including an undersea connection to the transmission network. Connections on a generation curtailment scheme are described as non-firm connections as they do not guarantee network access at all times. Generation curtailment and other ANM techniques provide an alternative to reinforcing www.ietdl.org

Potential value of energy storage in the UK electricity system

“…For the impact of the round-trip efficiency, as discussed by (Gill, et al, 2013), negative prices may provide incentives to increase losses. Hence, ES with lower energy efficiency could obtain a higher value.…”

“…The analysis in (Pudjianto, et al, 2014) shows the benefits of ES in supporting the distribution network; while ES is applied to increase the revenue for non-firm wind generation in (Gill, et al, 2013). This paper focuses on an assessment of the value that distributed ES may deliver to the owner in various applications.…”

Business cases for energy storage with multiple service provision

“…Further, the application of ES in distribution network is reviewed in [9]. The analysis in [10,11] shows the benefits of ES to increase the revenue for the non-firm distributed renewable generation.…”

Optimal air-conditioning load control in distribution network with intermittent renewables

“…The objective function is represented as (11), aiming to minimize the system operation costs. The net cost in this distribution network is decided by the real-time power exchange between external grid and demand side, and realtime electricity retail price with net feed in tariff.…”

“…In [10], the authors presented an approach to minimize the expected operational cost of the microgrid and power losses while accommodating the intermittent nature of renewable energy resources. In [11], energy storage was utilized to increase wind power penetration level and curtail peak load with revenue optimization taken into consideration. In [12], the authors proposed a direct load control scheme for the ACLs based on the distributed imperialist competitive algorithm to minimize total operation cost over the whole dispatch horizon.…”