Well, yes, of course. But let's start by checking what energy "market" you are considering? Is it "market exchange" or not?
Smart grid is more complicated and so-more expensive. The efficiency of generation and utilization of energy in near to zero homes is higher-so energy there is more cheep. Higher penetration of renewable energy sources is connected with increase of price of energy. Totaly, energy will be with increased price, but use of fossil energy will be lower
Future smart grids will require a flexible, observable, and controllable network for reliable and efficient energy delivery under uncertain generation and demand conditions. One of the mechanisms for efficient and reliable energy generation is dynamic demand-responsive generation management based on energy price adjustments that creates a balance in energy markets. This study [in attash] presents a closed-loop PID (proportional–integral–derivative) controller-based price control method for autonomous and real-time balancing of energy demand and generation in smart grid electricity markets. The PID control system can regulate energy prices online to respond dynamically and instantaneously to the varying energy demands of grid consumers. Independent energy suppliers in the smart grid decide whether to sell their energy to the grid according to the energy prices declared by the closed-loop PID controller system. Energy market simulations demonstrate that PID-controlled energy price regulation can effectively maintain an energy balance for hourly demand fluctuations of consumers.
Article A closed-loop energy price controlling method for real-time ...
This study investigates dynamic energy price regulation by a closed-loop fractional-order PI control system and presents a possible application for the automated energy balancing in smart grid energy markets. A persistent balance of energy demand and generation is a substantial problem for future smart grids due to the uncertainty and high fluctuation in the generation of distributed renewable energy sources and elastic demand conditions. Dynamic energy pricing is an effective strategy to balance flexible energy markets and it can provide the best energy price that balances energy demand and generation. We numerically demonstrate that closed-loop generation control by using dynamic pricing can provide persistent settling to the best price point of demand and supply curves, when the energy balance error is defined as the difference between instant demand and generation potentials. We analyse energy market management performance of a fractional-order PI controller in the case of communication and operation delays in a multi-source energy market model. Market simulation results are discussed to demonstrate the possible advantages of the fractional-order PI controller for smart grid energy market managements.
http://tim.sagepub.com/content/early/2015/04/11/0142331215579949.abstract
Closed loop elastic demand control by dynamic energy pricing in smart grids
Broadcasting of dynamic energy price signals for consumer's demand response programs (agents) is an effective and feasible way for demand side load management in future smart grids. Particularly, under fluctuating generation conditions of distributed renewable sources, automated and online market management strategies based on dynamic pricing are necessary for persistently conservation of energy balance and reducing the risk of instant energy shortages in the smart grids. This study presents a control theoretic energy market management approach based on closed loop elastic demand control scheme by means of dynamic price signal broadcasting. A PI controller structure is used to regulate energy price signals for demand response agents of smart grid community. Thus, total energy demand can be governed to respond fluctuation of renewable energy generation. To illustrate an application, a renewable energy integrated microgrid management scenario was studied numerically. A first order dynamic system model with a piecewise linear price-demand response is used to represent overall demand elasticity of the microgrid and a renewable energy microgrid simulation scenario is developed in Matlab/Simulink simulation environment. Simulation of 90 MWh peak demand market demonstrate that the closed loop dynamic energy pricing can be useful to control the elastic demand for tracing fluctuating generation of renewable energy sources. It is concluded that dynamic energy pricing can be useful medium for energy demand control.
https://www.sciencedirect.com/science/article/abs/pii/S0360544219306590
(see up to June 01, 2019 )
https://authors.elsevier.com/a/1Ytkl1H~c~7XfU
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