A home energy management systems (HEMSs)  is a smart home automatic control system that can optimally control residential appliances to serve multiple objectives (e.g., electricity cost minimization, peak load minimization) of residential customers while maintaining the customer’s thermal comfort in the presence of uncertain weather and electricity consumption.

From the perspective of the utility, widely distributed HEMSs in residential areas can serve as demand response (DR) providers, which shift the load to non-peak hours and minimize voltage violations and line congestions .

From the perspective of homeowners, HEMSs are developed to optimize forward-looking schedules for a residential home’s appliances, such as heating, ventilation, and air-conditioning (HVAC), refrigerator, water heater (WH), rooftop solar, energy storage (ES), lighting, and electric vehicle (EV).

As HEMSs are implemented in homes as ways of reducing customer costs and providing demand response (DR) to the electric utility, homeowner’s privacy should not be compromised. As part of the HEMS framework, homeowners are required to send load forecasts to the distribution system operator (DSO) for power balancing purposes. Submitting forecasts securely prevent attackers to gain knowledge on user patterns based on the load information provided.

The attacker could, for example, enter the home to steal valuable possessions when the homeowner is away if HEMS framework would not be secured accordingly. The data safety is key in a various new HEMS frameworks in order to maintain highest privacy standards. For example, some HEMS producers are exploring the ways to keep customer information private by utilising a smart contracts when communicating with the DSO.

Ideally, this concept should be implemented in a private blockchain, where user access is controlled. Note, in proposed private blockchain framework, the DSO and users’ addresses will be known and permissioned accordingly. Addresses are assigned to each user and DSO through a claiming framework. The procedure is implemented by using function calls ‘claimDSO()’ and ‘claimUser()’, with each input being a unique address in the blockchain. Each type is allowed specific permissions by function call ‘submitPrice()’. These values are used by each HEMS to optimize their load forecast schedule for the next timeslot based on this electricity price range. These values are obtainable by function call ‘getPrice()’. Once this is completed, each homeowner submits a range of forecasted demand data for the next timeslot. Forecasts are formatted as a lower and upper bound of the forecasted demand and sent to the smart contract through function call ‘submitRange()’. HEMS users must encrypt this data as it is publicly published on the blockchain. Prior to encryption, it would be published in the block in hexadecimal format, as depicted in Table I.

After all HEMSs in a bus have submitted their load ranges, the DSO calls function ‘getAgg()’ in the smart contract to aggregate the decrypted total load range in a single bus. Picture bellow provides the transaction event details of calling this function.

The data displays only the sum of the users’ forecasts and not individual load forecast values. Ideally, the smart contract would operate after a certain amount of time, even if all users had not submitted their forecasts. Offline, the DSO calculates the optimized allowed demand to each home using the aggregated demand range. The DSO then submits the optimal allowed power signal (𝜆) to the blockchain, using ‘submitLambda()’. At each new timeslot, each homeowner requests this value through another function in the contract, called ‘getLambda()’. The lambda value allows each HEMS owner to know their maximum allowable demand for the next timeslot. The DSO then clears all submitted values from the contract using ‘clearPrice()’, ‘clearRange()’, and ‘clearLambda()’ to prepare for the new submissions in the next timeslot. This process is repeated every timeslot.

Results show the homeowner’s privacy is maintained as their load forecasts are encrypted, and the total forecasted load in a node is aggregated and sent to the DSO through the blockchain. The DSO is also able to communicate the allowable load to each homeowner for the next timeslot in a secure manner.

The importance of data privacy is paramount in development of future smart cities equipped with smart home energy management systems (HEMSs) which have the auspicious potential to play a pivotal role in reducing global energy consumption while maintaining economic, reliable, and secure power grid operations.