Increase in the deployment of Distributed Energy Resources (DERs) has triggered a new trend to redesign electricity markets as consumer-centric markets relying on Peer-to-Peer (P2P) approaches. In the P2P markets, players can directly negotiate under bilateral energy trading to match demand and supply. The trading scheme should be designed adequately to incentivise players to participate in the trading process actively. This paper proposes a decentralised P2P energy trading scheme for electricity markets with high penetration of DERs. A novel algorithm using primal-dual gradient method is described to clear the market in a fully decentralised manner without interaction of any central entity. Also, to incorporate technical constraints in the energy trading, line flow constraints are modelled in the bilateral energy trading to avoid overloaded or congested lines in the system. This market structure respects market players' preferences by allowing bilateral energy trading with product differentiation. The performance of the proposed method is evaluated using simulation studies, and it is found that market players can trade energy to maximise their welfare without violating line flow constraints. Also, compared with other similar methods for P2P trading, the proposed approach needs lower data exchange and has a faster convergence rate.

Increasing penetration of photovoltaic (PV), as well as increasing peak load demand, has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and battery energy storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop-based BES system is evaluated for rural and urban scenarios (having different \mbi R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low-resistance feeder), whereas coordinated PV and BES support is required for the rural scenario (high-resistance feeder). Constant, as well as variable, droop-based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes are presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data are used to verify the efficacy of the proposed method.

Massive deployment of distributed energy resources (DERs) along with innovations in information and communication technologies have changed the power system from a hierarchical structure to a more deregulated model by introducing new generations at lower levels. This change raises operational and market challenges. Local energy trading provides opportunities to manage these DERs by encouraging localised trading. The concept of local energy trading at the distribution level is widely broadcasted for implementation in the power system. In the design of electricity markets for local energy trading, a clear definition of market participants, their objective, and purpose of market clearing should be established. This design depends on the changing needs of the power system and can be performed from different viewpoints. Classification and organisation of the literature on potential designs for local energy trading can help researchers to develop their future steps properly. This study presents a comprehensive review on this topic and provides a systematic classification of the market players, market clearing objectives, and approaches. Several research works are analysed against different criteria, including scalability, overheads requirements, and network constraints management.

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.